title
Supervised vs Unsupervised vs Reinforcement Learning | Data Science Certification Training | Edureka

description
🔥 Python Data Science Training (Use Code "𝐘𝐎𝐔𝐓𝐔𝐁𝐄𝟐𝟎"): https://www.edureka.co/data-science-python-certification-course In this video on Supervised vs Unsupervised vs Reinforcement learning, we’ll be discussing the types of machine learning and we’ll differentiate them based on a few key parameters. The following topics are covered in this session: 1. Introduction to Machine Learning 2. Types of Machine Learning 3. Supervised vs Unsupervised vs Reinforcement learning 4. Use Cases Python Training Playlist: https://goo.gl/Na1p9G Python Blog Series: https://bit.ly/2RVzcVE PG in Artificial Intelligence and Machine Learning with NIT Warangal : https://www.edureka.co/post-graduate/machine-learning-and-ai Post Graduate Certification in Data Science with IIT Guwahati - https://www.edureka.co/post-graduate/data-science-program (450+ Hrs || 9 Months || 20+ Projects & 100+ Case studies) - - - - - - - - - - - - - - - - - Subscribe to our channel to get video updates. Hit the subscribe button above: https://goo.gl/6ohpTV Instagram: https://www.instagram.com/edureka_learning/ Facebook: https://www.facebook.com/edurekaIN/ Twitter: https://twitter.com/edurekain LinkedIn: https://www.linkedin.com/company/edureka - - - - - - - - - - - - - - - - - How it Works? 1. This is a 5 Week Instructor led Online Course,40 hours of assignment and 20 hours of project work 2. We have a 24x7 One-on-One LIVE Technical Support to help you with any problems you might face or any clarifications you may require during the course. 3. At the end of the training, you will be working on a real-time project for which we will provide you a Grade and a Verifiable Certificate! - - - - - - - - - - - - - - - - - About the Course Edureka’s Data Science Course on Python helps you gain expertise in various machine learning algorithms such as regression, clustering, decision trees, random forest, Naïve Bayes and Q-Learning. Throughout the Data Science Certification Course, you’ll be solving real life case studies on Media, Healthcare, Social Media, Aviation, HR. During our Python Certification Training, our instructors will help you to: 1. Master the basic and advanced concepts of Python 2. Gain insight into the 'Roles' played by a Machine Learning Engineer 3. Automate data analysis using python 4. Gain expertise in machine learning using Python and build a Real Life Machine Learning application 5. Understand the supervised and unsupervised learning and concepts of Scikit-Learn 6. Explain Time Series and it’s related concepts 7. Perform Text Mining and Sentimental analysis 8. Gain expertise to handle business in the future, living the present 9. Work on a Real Life Project on Big Data Analytics using Python and gain Hands-on Project Experience - - - - - - - - - - - - - - - - - - - Why learn Python? Programmers love Python because of how fast and easy it is to use. Python cuts development time in half with its simple to read syntax and easy compilation feature. Debugging your programs is a breeze in Python with its built in debugger. Using Python makes Programmers more productive and their programs ultimately better. Python continues to be a favorite option for data scientists who use it for building and using Machine learning applications and other scientific computations. Python runs on Windows, Linux/Unix, Mac OS and has been ported to Java and .NET virtual machines. Python is free to use, even for the commercial products, because of its OSI-approved open source license. Python has evolved as the most preferred Language for Data Analytics and the increasing search trends on python also indicates that Python is the next "Big Thing" and a must for Professionals in the Data Analytics domain. For online Data Science training, please write back to us at sales@edureka.co or call us at IND: 9606058406 / US: 18338555775 (toll-free) for more information.

detail
{'title': 'Supervised vs Unsupervised vs Reinforcement Learning | Data Science Certification Training | Edureka', 'heatmap': [{'end': 200.029, 'start': 138.914, 'weight': 0.796}, {'end': 351.588, 'start': 303.285, 'weight': 0.748}, {'end': 424.235, 'start': 394.279, 'weight': 0.73}, {'end': 895.49, 'start': 865.985, 'weight': 0.733}], 'summary': 'Covers the evolution of ai and machine learning, explaining supervised, unsupervised, and reinforcement learning, along with their applications including business forecasting, recommendation systems, and self-driving cars.', 'chapters': [{'end': 236.847, 'segs': [{'end': 42.503, 'src': 'embed', 'start': 11.198, 'weight': 0, 'content': [{'end': 13.439, 'text': 'Hi guys, this is Zulekha from Edureka.', 'start': 11.198, 'duration': 2.241}, {'end': 17.661, 'text': 'The evolution of AI has changed the entire 21st century.', 'start': 14.079, 'duration': 3.582}, {'end': 23.643, 'text': 'In terms of technology, AI has stolen the spotlight and its advancements are quicker than we predicted.', 'start': 18.141, 'duration': 5.502}, {'end': 30.486, 'text': 'With such an exponential growth in AI, machine learning is becoming the most trending field of the 21st century.', 'start': 24.264, 'duration': 6.222}, {'end': 36.589, 'text': "It is starting to redefine the way we live and it's time we understood what it is and why it matters.", 'start': 31.067, 'duration': 5.522}, {'end': 42.503, 'text': "In this session, we'll be discussing the different types of machine learning and we'll compare them to each other.", 'start': 37.302, 'duration': 5.201}], 'summary': 'Ai has transformed the 21st century, with rapid advancements in machine learning redefining our lives.', 'duration': 31.305, 'max_score': 11.198, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/xtOg44r6dsE/pics/xtOg44r6dsE11198.jpg'}, {'end': 87.824, 'src': 'embed', 'start': 52.005, 'weight': 1, 'content': [{'end': 58.067, 'text': "After that, we'll compare supervised, unsupervised, and reinforcement learning based on a few key parameters.", 'start': 52.005, 'duration': 6.062}, {'end': 64.134, 'text': "We'll finally end the session by discussing a few example problems that can be solved using supervised,", 'start': 58.812, 'duration': 5.322}, {'end': 66.875, 'text': 'unsupervised and reinforcement learning algorithms.', 'start': 64.134, 'duration': 2.741}, {'end': 69.837, 'text': "So without any further delay, let's get started.", 'start': 67.556, 'duration': 2.281}, {'end': 78.8, 'text': 'So guys, machine learning is the science of getting computers to act by feeding them data and letting them learn a few tricks on their own,', 'start': 70.517, 'duration': 8.283}, {'end': 80.861, 'text': 'without being explicitly programmed.', 'start': 78.8, 'duration': 2.061}, {'end': 84.022, 'text': 'Now this sounds awfully a lot like a human child.', 'start': 81.401, 'duration': 2.621}, {'end': 87.824, 'text': "So let's consider a small scenario to understand machine learning.", 'start': 84.603, 'duration': 3.221}], 'summary': 'Comparison of supervised, unsupervised, and reinforcement learning, and examples of problems solved using these algorithms.', 'duration': 35.819, 'max_score': 52.005, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/xtOg44r6dsE/pics/xtOg44r6dsE52005.jpg'}, {'end': 215.077, 'src': 'heatmap', 'start': 138.914, 'weight': 3, 'content': [{'end': 142.655, 'text': "Now let's move ahead and take a look at the different types of machine learning.", 'start': 138.914, 'duration': 3.741}, {'end': 145.616, 'text': 'So first of all, we have supervised learning.', 'start': 143.555, 'duration': 2.061}, {'end': 152.086, 'text': "Now guys, supervised means to oversee or direct a certain activity and make sure it's done correctly.", 'start': 146.204, 'duration': 5.882}, {'end': 155.827, 'text': 'In this type of learning, the machine learns under guidance.', 'start': 152.866, 'duration': 2.961}, {'end': 159.248, 'text': 'So at school, our teachers guided us and taught us.', 'start': 156.407, 'duration': 2.841}, {'end': 166.309, 'text': 'Similarly, in supervised learning machines learn by feeding them labeled data and explicitly telling them hey,', 'start': 159.808, 'duration': 6.501}, {'end': 169.75, 'text': 'this is the input and this is exactly how the output must look.', 'start': 166.309, 'duration': 3.441}, {'end': 172.811, 'text': 'Okay, so the teacher in this case is the training data.', 'start': 170.091, 'duration': 2.72}, {'end': 175.392, 'text': 'Next, we have unsupervised learning.', 'start': 173.511, 'duration': 1.881}, {'end': 181.294, 'text': "Unsupervised means to act without anyone supervision or without anybody's direction.", 'start': 176.13, 'duration': 5.164}, {'end': 183.696, 'text': 'Now here the data is not labeled.', 'start': 181.915, 'duration': 1.781}, {'end': 192.163, 'text': 'There is no guide and the machine has to figure out the data set given and it has to find hidden patterns in order to make predictions about the output.', 'start': 184.177, 'duration': 7.986}, {'end': 196.566, 'text': 'An example of unsupervised learning is an adult like you and me.', 'start': 192.823, 'duration': 3.743}, {'end': 200.029, 'text': "We don't need a guide to help us with our daily activities.", 'start': 197.167, 'duration': 2.862}, {'end': 203.372, 'text': 'We can figure things out on our own without any supervision.', 'start': 200.45, 'duration': 2.922}, {'end': 206.274, 'text': 'Finally, we have reinforcement learning.', 'start': 204.073, 'duration': 2.201}, {'end': 211.456, 'text': 'Now guys, reinforcement means to establish or encourage a pattern of behavior.', 'start': 206.794, 'duration': 4.662}, {'end': 215.077, 'text': "Let's say that you were dropped off at an isolated island.", 'start': 212.076, 'duration': 3.001}], 'summary': 'Transcript explains supervised, unsupervised, and reinforcement learning with relatable examples.', 'duration': 90.207, 'max_score': 138.914, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/xtOg44r6dsE/pics/xtOg44r6dsE138914.jpg'}], 'start': 11.198, 'title': 'Evolution of ai and machine learning', 'summary': 'Explores the exponential growth of ai, its impact on technology, and the different types of machine learning - supervised learning, unsupervised learning, and reinforcement learning.', 'chapters': [{'end': 105.472, 'start': 11.198, 'title': 'Evolution of ai and machine learning', 'summary': 'Explores the exponential growth of ai and its impact on technology, highlighting its role in redefining the 21st century, with a focus on machine learning types and their comparison based on key parameters.', 'duration': 94.274, 'highlights': ["AI has stolen the spotlight with quicker-than-predicted advancements, making machine learning the most trending field of the 21st century. AI's exponential growth in technology is redefining the 21st century, with machine learning emerging as the leading field.", 'Discussion on the different types of machine learning and comparison between supervised, unsupervised, and reinforcement learning based on key parameters. The session covers an introduction to machine learning, types of machine learning, and a comparison of supervised, unsupervised, and reinforcement learning based on key parameters.', 'Machine learning is the science of getting computers to act by learning from data without being explicitly programmed, akin to human learning. Machine learning enables computers to learn from data without explicit programming, similar to human learning.']}, {'end': 236.847, 'start': 106.133, 'title': 'Types of machine learning', 'summary': 'Explains the concept of machine learning, its working principle, and the different types of machine learning - supervised learning, unsupervised learning, and reinforcement learning, drawing parallels with human learning processes.', 'duration': 130.714, 'highlights': ['Machine learning involves continuously feeding data to a machine so that it can interpret this data, understand the useful insights, detect patterns and identify key features to solve problems, similar to how our brain works. Machine learning involves continuous data feeding to interpret insights and detect patterns, analogous to human brain functions.', "Supervised learning involves machines learning under guidance by feeding them labeled data and explicitly telling them the input and the expected output, similar to how teachers guide and teach students. Supervised learning involves guidance through labeled data, akin to how teachers guide students' learning.", 'Unsupervised learning involves the machine figuring out the data set and finding hidden patterns without any guide, drawing a parallel with adults figuring things out without any supervision. Unsupervised learning involves finding hidden patterns without guidance, akin to how adults figure things out without supervision.', 'Reinforcement learning involves learning through adaptation and hit-and-trial, similar to how a person would adapt and learn to survive on an isolated island. Reinforcement learning involves learning through adaptation, similar to survival learning on an isolated island.']}], 'duration': 225.649, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/xtOg44r6dsE/pics/xtOg44r6dsE11198.jpg', 'highlights': ["AI's exponential growth in technology is redefining the 21st century, with machine learning emerging as the leading field.", 'Discussion on the different types of machine learning and comparison between supervised, unsupervised, and reinforcement learning based on key parameters.', 'Machine learning enables computers to learn from data without explicit programming, similar to human learning.', 'Machine learning involves continuous data feeding to interpret insights and detect patterns, analogous to human brain functions.', "Supervised learning involves guidance through labeled data, akin to how teachers guide students' learning.", 'Unsupervised learning involves finding hidden patterns without guidance, akin to how adults figure things out without supervision.', 'Reinforcement learning involves learning through adaptation, similar to survival learning on an isolated island.']}, {'end': 836.663, 'segs': [{'end': 262.861, 'src': 'embed', 'start': 236.847, 'weight': 0, 'content': [{'end': 242.91, 'text': "because you're new to the surrounding and the only way to learn is experience and then learn from your experience.", 'start': 236.847, 'duration': 6.063}, {'end': 245.171, 'text': 'This is what reinforcement learning is.', 'start': 243.43, 'duration': 1.741}, {'end': 254.436, 'text': 'It is a learning method wherein an agent, which is basically you stuck on the island, interacts with its environment, which is the island,', 'start': 245.912, 'duration': 8.524}, {'end': 257.778, 'text': 'by producing actions and discovers errors or rewards.', 'start': 254.436, 'duration': 3.342}, {'end': 262.861, 'text': 'And once the agent gets trained, it gets ready to predict the new data presented to it.', 'start': 258.439, 'duration': 4.422}], 'summary': 'Reinforcement learning involves an agent interacting with its environment to learn and predict new data.', 'duration': 26.014, 'max_score': 236.847, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/xtOg44r6dsE/pics/xtOg44r6dsE236847.jpg'}, {'end': 378.867, 'src': 'heatmap', 'start': 303.285, 'weight': 1, 'content': [{'end': 305.968, 'text': 'Now this agent is put in an unknown environment.', 'start': 303.285, 'duration': 2.683}, {'end': 313.696, 'text': 'So the agent has to explore the environment by taking actions and transitioning from one state to the other so that he can get maximum rewards.', 'start': 306.268, 'duration': 7.428}, {'end': 321.679, 'text': 'Now the next parameter to consider is the type of problems that are solved using supervised unsupervised and reinforcement learning.', 'start': 314.395, 'duration': 7.284}, {'end': 326.141, 'text': 'So under supervised learning we have two main categories of problems.', 'start': 322.339, 'duration': 3.802}, {'end': 329.883, 'text': 'We have regression problems and we have classification problems.', 'start': 326.741, 'duration': 3.142}, {'end': 334.105, 'text': "Now guys, there's an important difference between classification and regression.", 'start': 330.463, 'duration': 3.642}, {'end': 342.169, 'text': 'Basically classification is about predicting a label or a class whereas regression is about predicting a continuous quantity.', 'start': 334.825, 'duration': 7.344}, {'end': 346.465, 'text': "Now let's say that you have to classify your emails into two different groups.", 'start': 342.862, 'duration': 3.603}, {'end': 351.588, 'text': "So here basically we'll be labeling our emails as spam and non-spam mails.", 'start': 347.245, 'duration': 4.343}, {'end': 359.573, 'text': 'For this kind of problem where we have to assign our input data into different classes, we make use of classification algorithms.', 'start': 352.349, 'duration': 7.224}, {'end': 364.097, 'text': 'On the other hand, regression is used to predict a continuous quantity.', 'start': 360.214, 'duration': 3.883}, {'end': 369.48, 'text': 'Now a continuous variable is a variable that has infinite number of possibilities.', 'start': 364.697, 'duration': 4.783}, {'end': 371.762, 'text': "For example, a person's weight.", 'start': 370.061, 'duration': 1.701}, {'end': 378.867, 'text': 'So someone could be 180 pounds or they could be 180.10 pounds or 180.110 pounds.', 'start': 372.302, 'duration': 6.565}], 'summary': 'Agent explores unknown environment to maximize rewards, while supervised learning involves classification and regression problems.', 'duration': 75.582, 'max_score': 303.285, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/xtOg44r6dsE/pics/xtOg44r6dsE303285.jpg'}, {'end': 424.235, 'src': 'heatmap', 'start': 394.279, 'weight': 0.73, 'content': [{'end': 400.702, 'text': "Instead, you have to predict a final outcome like let's say that you want to predict the price of a stock over a period of time.", 'start': 394.279, 'duration': 6.423}, {'end': 404.164, 'text': 'For such problems, you can make use of regression algorithms.', 'start': 401.182, 'duration': 2.982}, {'end': 411.307, 'text': 'Coming to unsupervised learning, this type of learning can be used to solve association problems and clustering problems.', 'start': 404.844, 'duration': 6.463}, {'end': 418.19, 'text': 'Association problems basically involve discovering patterns in data, finding co-occurrences and so on.', 'start': 412.027, 'duration': 6.163}, {'end': 424.235, 'text': 'A classic example of association rule mining is a relationship between bread and jam.', 'start': 419.091, 'duration': 5.144}], 'summary': 'Predict stock price with regression, use unsupervised learning for association and clustering', 'duration': 29.956, 'max_score': 394.279, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/xtOg44r6dsE/pics/xtOg44r6dsE394279.jpg'}, {'end': 464.07, 'src': 'embed', 'start': 436.064, 'weight': 2, 'content': [{'end': 441.848, 'text': 'Apart from association problems, unsupervised learning also deals with clustering and anomaly detection problems.', 'start': 436.064, 'duration': 5.784}, {'end': 450.339, 'text': 'Clustering is used for cases that involve targeted marketing wherein you are given a list of customers and some information about them.', 'start': 442.893, 'duration': 7.446}, {'end': 455.163, 'text': 'And what you have to do is you have to cluster these customers based on their similarity.', 'start': 450.999, 'duration': 4.164}, {'end': 464.07, 'text': 'Now guys, digital ad words use a clustering technique to cluster potential buyers into different categories based on their interests and their intent.', 'start': 455.883, 'duration': 8.187}], 'summary': 'Unsupervised learning includes clustering and anomaly detection. clustering is used in targeted marketing to group customers based on similarity. digital ad words use clustering to categorize potential buyers.', 'duration': 28.006, 'max_score': 436.064, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/xtOg44r6dsE/pics/xtOg44r6dsE436064.jpg'}, {'end': 591.713, 'src': 'embed', 'start': 567.318, 'weight': 4, 'content': [{'end': 573.783, 'text': 'But a point to remember here is that in the training phase for a supervised learning algorithm, the data is labeled.', 'start': 567.318, 'duration': 6.465}, {'end': 577.246, 'text': 'The input is also labeled and the output is also labeled.', 'start': 574.243, 'duration': 3.003}, {'end': 581.569, 'text': 'In unsupervised learning, the machine is only given the input data.', 'start': 578.146, 'duration': 3.423}, {'end': 584.267, 'text': "So here we don't tell the system where to go.", 'start': 582.225, 'duration': 2.042}, {'end': 588.45, 'text': 'The system has to understand itself from the input data that we give to it.', 'start': 584.287, 'duration': 4.163}, {'end': 591.713, 'text': 'So it does this by finding patterns in the data.', 'start': 589.191, 'duration': 2.522}], 'summary': 'Supervised learning uses labeled data, while unsupervised learning finds patterns in unlabeled data.', 'duration': 24.395, 'max_score': 567.318, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/xtOg44r6dsE/pics/xtOg44r6dsE567318.jpg'}, {'end': 659.728, 'src': 'embed', 'start': 629.372, 'weight': 3, 'content': [{'end': 635.576, 'text': 'So basically, as the agent explores the environment, it will collect data which will then be used to get the output.', 'start': 629.372, 'duration': 6.204}, {'end': 640.398, 'text': 'So guys, in reinforcement learning, there is no predefined data set given to the machine.', 'start': 636.156, 'duration': 4.242}, {'end': 642.88, 'text': 'The agent does all the work from scratch.', 'start': 640.859, 'duration': 2.021}, {'end': 645.701, 'text': 'The next parameter to consider is training.', 'start': 643.62, 'duration': 2.081}, {'end': 650.164, 'text': 'In supervised learning, the training phase is well-defined and very explicit.', 'start': 646.442, 'duration': 3.722}, {'end': 659.728, 'text': 'The machine is fed training data where both the input and output is labeled and the only thing the algorithm has to do is map the input to the output.', 'start': 650.845, 'duration': 8.883}], 'summary': 'In reinforcement learning, the agent collects data to generate output without a predefined dataset, unlike supervised learning.', 'duration': 30.356, 'max_score': 629.372, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/xtOg44r6dsE/pics/xtOg44r6dsE629372.jpg'}, {'end': 814.33, 'src': 'embed', 'start': 768.687, 'weight': 5, 'content': [{'end': 776.195, 'text': 'In unsupervised learning, the algorithm has to find patterns in data, trends in data, and keep exploring the data until it reaches the output.', 'start': 768.687, 'duration': 7.508}, {'end': 781.16, 'text': 'The approach followed by reinforcement learning is a trial and error method.', 'start': 777.016, 'duration': 4.144}, {'end': 785.769, 'text': 'The trial and error method best explains reinforcement learning,', 'start': 781.886, 'duration': 3.883}, {'end': 792.095, 'text': 'because the agent has to try out all possible actions to learn about its environment and to get maximum rewards.', 'start': 785.769, 'duration': 6.326}, {'end': 794.597, 'text': 'The next parameter is feedback.', 'start': 792.815, 'duration': 1.782}, {'end': 801.643, 'text': 'Now in supervised learning, there is a direct feedback mechanism since the machine is trained with labeled input and output.', 'start': 795.198, 'duration': 6.445}, {'end': 808.389, 'text': 'For unsupervised learning, there is no feedback mechanism because the machine is unaware of the output during the training phase.', 'start': 802.444, 'duration': 5.945}, {'end': 814.33, 'text': 'Now in reinforcement learning the feedback is in the form of rewards or punishments from the environment.', 'start': 809.207, 'duration': 5.123}], 'summary': 'Unsupervised learning finds patterns, reinforcement learning is trial and error, supervised learning has direct feedback.', 'duration': 45.643, 'max_score': 768.687, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/xtOg44r6dsE/pics/xtOg44r6dsE768687.jpg'}], 'start': 236.847, 'title': 'Machine learning overview', 'summary': 'Provides an overview of reinforcement learning as a method for learning from experience, and discusses the differences between supervised, unsupervised, and reinforcement learning, including their input, training phase, aim, and feedback mechanisms.', 'chapters': [{'end': 479.349, 'start': 236.847, 'title': 'Reinforcement learning overview', 'summary': 'Explains reinforcement learning as a method where an agent interacts with its environment to learn from experience, while also covering the differences between supervised, unsupervised, and reinforcement learning, and the types of problems they solve.', 'duration': 242.502, 'highlights': ['Reinforcement learning is a learning method where an agent interacts with its environment to discover errors or rewards. Reinforcement learning involves an agent interacting with its environment to maximize rewards, serving as a method to learn from experience.', 'Supervised learning involves teaching the machine using labeled data for regression and classification problems. Supervised learning utilizes labeled data for regression and classification problems, predicting continuous quantities and assigning inputs into different classes respectively.', 'Unsupervised learning can be used for association problems, clustering, and anomaly detection. Unsupervised learning is applicable for association problems, clustering, and anomaly detection, discovering patterns, clustering similar items, and detecting unusual activities.']}, {'end': 836.663, 'start': 480.069, 'title': 'Types of machine learning', 'summary': 'Discusses the differences between supervised, unsupervised, and reinforcement learning, highlighting how they differ in input, training phase, aim, and feedback mechanisms, with reinforcement learning being more exploratory and reward-based compared to the other two.', 'duration': 356.594, 'highlights': ['Reinforcement learning is characterized by input depending on the actions taken by the agent, and the agent learning through exploration and collecting data, without predefined data sets. input depending on actions taken, exploration and data collection, no predefined data sets', 'In supervised learning, the machine is provided with labeled input and output data in the training phase, whereas in unsupervised learning, the machine is only given the input data and has to figure out the output on its own by finding patterns in the data. labeled input and output data, finding patterns in input data', 'Reinforcement learning uses a trial and error approach, where the agent tries out all possible actions to learn about its environment and maximize rewards, while supervised learning involves mapping known input to known output, and unsupervised learning focuses on finding patterns and trends in data. trial and error approach, mapping known input to known output, finding patterns and trends in data', "Feedback mechanisms vary among the three types: supervised learning has direct feedback with labeled input and output, unsupervised learning lacks a feedback mechanism, and reinforcement learning uses rewards and punishments from the environment based on the agent's actions. direct feedback with labeled input and output, lack of feedback mechanism, use of rewards and punishments"]}], 'duration': 599.816, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/xtOg44r6dsE/pics/xtOg44r6dsE236847.jpg', 'highlights': ['Reinforcement learning involves an agent interacting with its environment to maximize rewards, serving as a method to learn from experience.', 'Supervised learning utilizes labeled data for regression and classification problems, predicting continuous quantities and assigning inputs into different classes respectively.', 'Unsupervised learning is applicable for association problems, clustering, and anomaly detection, discovering patterns, clustering similar items, and detecting unusual activities.', 'Reinforcement learning is characterized by input depending on the actions taken by the agent, and the agent learning through exploration and collecting data, without predefined data sets.', 'In supervised learning, the machine is provided with labeled input and output data in the training phase, whereas in unsupervised learning, the machine is only given the input data and has to figure out the output on its own by finding patterns in the data.', 'Reinforcement learning uses a trial and error approach, where the agent tries out all possible actions to learn about its environment and maximize rewards, while supervised learning involves mapping known input to known output, and unsupervised learning focuses on finding patterns and trends in data.', "Feedback mechanisms vary among the three types: supervised learning has direct feedback with labeled input and output, unsupervised learning lacks a feedback mechanism, and reinforcement learning uses rewards and punishments from the environment based on the agent's actions."]}, {'end': 1163.008, 'segs': [{'end': 920.048, 'src': 'heatmap', 'start': 865.985, 'weight': 0, 'content': [{'end': 874.299, 'text': 'recently, A few algorithms include Q learning and the state action reward state action algorithm next up.', 'start': 865.985, 'duration': 8.314}, {'end': 875.64, 'text': 'We have applications.', 'start': 874.359, 'duration': 1.281}, {'end': 882.363, 'text': 'So guys, supervised learning is widely used in the business sector for forecasting risk, risk analysis,', 'start': 876.2, 'duration': 6.163}, {'end': 886.785, 'text': 'predicting sales profit and so on coming to unsupervised learning.', 'start': 882.363, 'duration': 4.422}, {'end': 895.49, 'text': 'So guys the recommendations you see when you shop online like for example, if you buy a book on Amazon right you get a list of recommendations.', 'start': 887.426, 'duration': 8.064}, {'end': 900.012, 'text': 'Now these are all done by unsupervised learning algorithms.', 'start': 896.09, 'duration': 3.922}, {'end': 905.375, 'text': 'other applications include anomaly detection, credit card fraud detection and so on.', 'start': 900.012, 'duration': 5.363}, {'end': 909.837, 'text': 'now reinforcement learning is used in self-driving cars, in building games and all of that.', 'start': 905.375, 'duration': 4.462}, {'end': 912.923, 'text': 'One famous example is the AlphaGo game.', 'start': 910.621, 'duration': 2.302}, {'end': 914.324, 'text': "I'm sure all of you have heard of that.", 'start': 913.063, 'duration': 1.261}, {'end': 920.048, 'text': 'So guys, those were the major differences between supervised, unsupervised, and reinforcement learning.', 'start': 914.844, 'duration': 5.204}], 'summary': 'Algorithms like q learning and sarsa have various applications, such as forecasting, risk analysis, and recommendation systems in supervised, unsupervised, and reinforcement learning.', 'duration': 43.848, 'max_score': 865.985, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/xtOg44r6dsE/pics/xtOg44r6dsE865985.jpg'}, {'end': 998.515, 'src': 'embed', 'start': 958.636, 'weight': 3, 'content': [{'end': 961.819, 'text': 'based on his purpose, his credit amount and his savings.', 'start': 958.636, 'duration': 3.183}, {'end': 969.975, 'text': 'So for this problem you can make use of the supervised learning algorithm known as KNN algorithm or k-nearest neighbor algorithm.', 'start': 962.668, 'duration': 7.307}, {'end': 972.217, 'text': "Now let's look at our next use case.", 'start': 970.615, 'duration': 1.602}, {'end': 978.042, 'text': 'Now here we have to establish a mathematical equation for distance as a function of speed.', 'start': 972.737, 'duration': 5.305}, {'end': 983.907, 'text': "So basically over here you're going to predict the distance that a car can travel based on its speed.", 'start': 978.662, 'duration': 5.245}, {'end': 989.633, 'text': 'So guys, the best algorithm to use for such a problem is the linear regression algorithm.', 'start': 984.992, 'duration': 4.641}, {'end': 994.354, 'text': 'So the linear regression algorithm is basically used to predict continuous quantities.', 'start': 990.133, 'duration': 4.221}, {'end': 998.515, 'text': 'And in this case, we have to predict the distance, which is a continuous quantity.', 'start': 994.994, 'duration': 3.521}], 'summary': 'Using knn for credit prediction, linear regression for distance prediction.', 'duration': 39.879, 'max_score': 958.636, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/xtOg44r6dsE/pics/xtOg44r6dsE958636.jpg'}, {'end': 1063.229, 'src': 'embed', 'start': 1019.522, 'weight': 5, 'content': [{'end': 1025.867, 'text': 'All right, this clearly means that this is a clustering problem and clustering problems fall under unsupervised learning.', 'start': 1019.522, 'duration': 6.345}, {'end': 1031.83, 'text': "So here we're gonna make use of algorithm known as k-means algorithm to form two clusters.", 'start': 1026.387, 'duration': 5.443}, {'end': 1039.797, 'text': 'Okay, one cluster is gonna contain popular movies and the other is gonna contain non-popular movies based on their likes on social media.', 'start': 1032.271, 'duration': 7.526}, {'end': 1049.442, 'text': 'Now moving ahead our next problem statement is to perform market basket analysis by finding association between items bought at the grocery store.', 'start': 1040.558, 'duration': 8.884}, {'end': 1052.504, 'text': 'Again over here you can see the keyword association.', 'start': 1050.023, 'duration': 2.481}, {'end': 1055.345, 'text': 'This means that this is an association problem.', 'start': 1053.164, 'duration': 2.181}, {'end': 1063.229, 'text': 'Now association problems fall under the unsupervised learning algorithms and here we can make use of the a priori algorithm to do this.', 'start': 1055.926, 'duration': 7.303}], 'summary': 'Using k-means to form 2 clusters of popular and non-popular movies, and a priori algorithm for market basket analysis.', 'duration': 43.707, 'max_score': 1019.522, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/xtOg44r6dsE/pics/xtOg44r6dsE1019522.jpg'}, {'end': 1132.845, 'src': 'embed', 'start': 1104.404, 'weight': 7, 'content': [{'end': 1109.889, 'text': 'To solve this you can make use of the Q learning algorithm and your end goal is to reach room number five.', 'start': 1104.404, 'duration': 5.485}, {'end': 1116.298, 'text': 'So guys here you can see that there is no data set because the data set is going to be developed by the agent itself.', 'start': 1110.552, 'duration': 5.746}, {'end': 1122.484, 'text': "So, guys over here, the agent is responsible for collecting the data, or that he's going to explore the environment,", 'start': 1117.159, 'duration': 5.325}, {'end': 1127.189, 'text': "collect useful information and then he's going to use this information to get to room number five.", 'start': 1122.484, 'duration': 4.705}, {'end': 1132.845, 'text': "So guys that was it for our use cases and with this we come to the end of today's video.", 'start': 1128.16, 'duration': 4.685}], 'summary': 'Using q learning, agent collects data to reach room five.', 'duration': 28.441, 'max_score': 1104.404, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/xtOg44r6dsE/pics/xtOg44r6dsE1104404.jpg'}], 'start': 837.606, 'title': 'Types of machine learning algorithms and use cases', 'summary': 'Discusses supervised, unsupervised, and reinforcement learning algorithms with applications in business forecasting, recommendation systems, and self-driving cars. it also covers specific use cases such as knn for credit prediction, linear regression for distance prediction, k-means for movie clustering, a priori for market basket analysis, and q learning for reinforcement learning.', 'chapters': [{'end': 958.636, 'start': 837.606, 'title': 'Types of machine learning algorithms', 'summary': 'Discusses the major types of machine learning algorithms, including supervised, unsupervised, and reinforcement learning, with applications in business forecasting, recommendation systems, and self-driving cars.', 'duration': 121.03, 'highlights': ['Supervised learning is widely used in the business sector for forecasting risk, risk analysis, and predicting sales profit. Supervised learning is applied in business for risk forecasting, risk analysis, and sales profit prediction.', 'Unsupervised learning algorithms are used for recommendation systems in e-commerce, anomaly detection, and credit card fraud detection. Unsupervised learning is utilized for e-commerce recommendations, anomaly detection, and credit card fraud detection.', 'Reinforcement learning is employed in self-driving cars and game development, such as the famous example of the AlphaGo game. Reinforcement learning is utilized in self-driving cars and game development, like the AlphaGo game.']}, {'end': 1163.008, 'start': 958.636, 'title': 'Machine learning use cases', 'summary': 'Covers various machine learning use cases including knn algorithm for credit prediction, linear regression for distance prediction, k-means algorithm for movie clustering, a priori algorithm for market basket analysis, and q learning algorithm for reinforcement learning.', 'duration': 204.372, 'highlights': ['KNN algorithm used for credit prediction based on purpose, credit amount, and savings. Supervised learning algorithm used to predict creditworthiness based on specific factors.', 'Linear regression algorithm applied to predict the distance a car can travel based on its speed. Supervised learning algorithm utilized for predicting continuous quantities such as distance based on specific parameters.', 'K-means algorithm used to cluster movies based on social media outreach. Unsupervised learning algorithm employed to categorize movies into popular and non-popular clusters based on social media likes.', 'A priori algorithm utilized for market basket analysis to find associations between items bought at a grocery store. Unsupervised learning algorithm used to identify associations between different items purchased together.', 'Q learning algorithm applied to solve the reinforcement learning problem of reaching room number five. Reinforcement learning algorithm used to enable an agent to explore and learn from its environment to achieve a specific goal.']}], 'duration': 325.402, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/xtOg44r6dsE/pics/xtOg44r6dsE837606.jpg', 'highlights': ['Supervised learning is widely used in the business sector for forecasting risk, risk analysis, and predicting sales profit.', 'Unsupervised learning algorithms are used for recommendation systems in e-commerce, anomaly detection, and credit card fraud detection.', 'Reinforcement learning is employed in self-driving cars and game development, such as the famous example of the AlphaGo game.', 'KNN algorithm used for credit prediction based on purpose, credit amount, and savings.', 'Linear regression algorithm applied to predict the distance a car can travel based on its speed.', 'K-means algorithm used to cluster movies based on social media outreach.', 'A priori algorithm utilized for market basket analysis to find associations between items bought at a grocery store.', 'Q learning algorithm applied to solve the reinforcement learning problem of reaching room number five.']}], 'highlights': ["AI's exponential growth in technology is redefining the 21st century, with machine learning emerging as the leading field.", 'Discussion on the different types of machine learning and comparison between supervised, unsupervised, and reinforcement learning based on key parameters.', 'Machine learning enables computers to learn from data without explicit programming, similar to human learning.', 'Machine learning involves continuous data feeding to interpret insights and detect patterns, analogous to human brain functions.', 'Reinforcement learning involves an agent interacting with its environment to maximize rewards, serving as a method to learn from experience.', 'Supervised learning utilizes labeled data for regression and classification problems, predicting continuous quantities and assigning inputs into different classes respectively.', 'Unsupervised learning is applicable for association problems, clustering, and anomaly detection, discovering patterns, clustering similar items, and detecting unusual activities.', 'Supervised learning is widely used in the business sector for forecasting risk, risk analysis, and predicting sales profit.', 'Unsupervised learning algorithms are used for recommendation systems in e-commerce, anomaly detection, and credit card fraud detection.', 'Reinforcement learning is employed in self-driving cars and game development, such as the famous example of the AlphaGo game.']}