title
What is Machine Learning? | Machine Learning Basics | Machine Learning Tutorial | Edureka

description
πŸ”₯Data Science Certification (Use Code "π˜πŽπ”π“π”ππ„πŸπŸŽ"): https://www.edureka.co/data-science-r-programming-certification-course This Edureka video on "What is Machine Learning" (Machine Learning Blog: https://goo.gl/fe7ykh ) gives an introduction to Machine Learning and its various types. Below are the topics covered in this tutorial: 1. Evolution of Machine Learning 2. What is Machine Learning? 3. Types of Machine Learning 4. Supervised Learning 5. Unsupervised Learning 6. Reinforcement Learning Subscribe to our channel to get video updates. Hit the subscribe button above. Machine Learning Tutorial Playlist: https://goo.gl/UxjTxm 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) #MachineLearning #PythonMachineLearning #PythonMachineTraining 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 Python Online Certification Training will make you an expert in Python programming. It will also help you learn Python the Big data way with integration of Machine learning, Pig, Hive and Web Scraping through beautiful soup. During our Python Certification training, our instructors will help you: 1. Master the Basic and Advanced Concepts of Python 2. Understand Python Scripts on UNIX/Windows, Python Editors and IDEs 3. Master the Concepts of Sequences and File operations 4. Learn how to use and create functions, sorting different elements, Lambda function, error handling techniques and Regular expressions ans using modules in Python 5. Gain expertise in machine learning using Python and build a Real Life Machine Learning application 6. Understand the supervised and unsupervised learning and concepts of Scikit-Learn 7. Master the concepts of MapReduce in Hadoop 8. Learn to write Complex MapReduce programs 9. Understand what is PIG and HIVE, Streaming feature in Hadoop, MapReduce job running with Python 10. Implementing a PIG UDF in Python, Writing a HIVE UDF in Python, Pydoop and/Or MRjob Basics 11. Master the concepts of Web scraping in Python 12. 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 more information, Please write back to us at sales@edureka.co or call us at IND: 9606058406 / US: 18338555775 (toll free). 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 Customer Review Sairaam Varadarajan, Data Evangelist at Medtronic, Tempe, Arizona: "I took Big Data and Hadoop / Python course and I am planning to take Apache Mahout thus becoming the "customer of Edureka!". Instructors are knowledge... able and interactive in teaching. The sessions are well structured with a proper content in helping us to dive into Big Data / Python. Most of the online courses are free, edureka charges a minimal amount. Its acceptable for their hard-work in tailoring - All new advanced courses and its specific usage in industry. I am confident that, no other website which have tailored the courses like Edureka. It will help for an immediate take-off in Data Science and Hadoop working."

detail
{'title': 'What is Machine Learning? | Machine Learning Basics | Machine Learning Tutorial | Edureka', 'heatmap': [{'end': 204.065, 'start': 155.639, 'weight': 0.749}, {'end': 842.84, 'start': 802.114, 'weight': 0.787}], 'summary': 'Covers machine learning fundamentals, supervised learning, and unsupervised & reinforcement learning, explaining their applications, differences, and use cases in sectors like banking and healthcare.', 'chapters': [{'end': 231.411, 'segs': [{'end': 139.724, 'src': 'embed', 'start': 4.226, 'weight': 0, 'content': [{'end': 4.867, 'text': 'Hello everyone.', 'start': 4.226, 'duration': 0.641}, {'end': 10.531, 'text': "This is Atul from Edureka and welcome to today's session on what is machine learning.", 'start': 5.267, 'duration': 5.264}, {'end': 13.673, 'text': 'as you know, we are living in a world of humans and machines.', 'start': 10.531, 'duration': 3.142}, {'end': 18.057, 'text': 'humans have been evolving and learning from the past experience since millions of years.', 'start': 13.673, 'duration': 4.384}, {'end': 23.601, 'text': "On the other hand the era of machines and robots have just begun in today's world.", 'start': 18.637, 'duration': 4.964}, {'end': 28.765, 'text': 'These machines or the robots are like they need to be programmed before they actually follow your instructions.', 'start': 23.862, 'duration': 4.903}, {'end': 31.748, 'text': 'But what if the machine started to learn on their own?', 'start': 29.426, 'duration': 2.322}, {'end': 35.788, 'text': 'and this is where machine learning comes into picture.', 'start': 32.725, 'duration': 3.063}, {'end': 40.653, 'text': 'machine learning is the core of many futuristic technological advancement in our world today.', 'start': 35.788, 'duration': 4.865}, {'end': 47.94, 'text': "You can see various examples or implementation of machine learning around us, such as Tesla's self-driving car, Apple Siri, Sofia,", 'start': 40.693, 'duration': 7.247}, {'end': 49.601, 'text': 'AI robot and many more are there.', 'start': 47.94, 'duration': 1.661}, {'end': 52.084, 'text': 'So what exactly is machine learning??', 'start': 50.282, 'duration': 1.802}, {'end': 63.354, 'text': 'Well, machine learning is a subfield of artificial intelligence that focuses on the design of system that can learn from and make decisions and predictions based on the experience,', 'start': 52.705, 'duration': 10.649}, {'end': 63.974, 'text': 'which is data.', 'start': 63.354, 'duration': 0.62}, {'end': 65.756, 'text': 'in the case of machines,', 'start': 63.974, 'duration': 1.782}, {'end': 73.282, 'text': 'machine learning enables computer to act and make data-driven decisions rather than being explicitly programmed to carry out a certain task.', 'start': 65.756, 'duration': 7.526}, {'end': 78.826, 'text': 'These programs are designed to learn and improve over time when exposed to new data.', 'start': 73.862, 'duration': 4.964}, {'end': 82.389, 'text': "let's move on and discuss one of the biggest confusion of the people in the world.", 'start': 78.826, 'duration': 3.563}, {'end': 88.224, 'text': 'They think that all the three of them the AI the machine learning and the deep learning all the same.', 'start': 82.941, 'duration': 5.283}, {'end': 89.825, 'text': 'You know what they are wrong.', 'start': 88.645, 'duration': 1.18}, {'end': 96.769, 'text': 'Let me clarify things for you artificial intelligence is a broader concept of machines being able to carry out task in a smarter way.', 'start': 90.105, 'duration': 6.664}, {'end': 101.232, 'text': 'It covers anything which enables the computer to behave like humans.', 'start': 97.31, 'duration': 3.922}, {'end': 106.375, 'text': 'think of a famous Turing test to determine whether a computer is capable of thinking like a human being or not.', 'start': 101.232, 'duration': 5.143}, {'end': 109.557, 'text': 'If you are talking to Siri on your phone and you get an answer.', 'start': 106.976, 'duration': 2.581}, {'end': 110.898, 'text': "You're already very close to it.", 'start': 109.617, 'duration': 1.281}, {'end': 115.813, 'text': 'So this was about the artificial intelligence now coming to the machine learning part.', 'start': 111.491, 'duration': 4.322}, {'end': 121.175, 'text': 'So as I already said machine learning is a subset or a current application of AI.', 'start': 116.533, 'duration': 4.642}, {'end': 127.478, 'text': 'It is based on the idea that we should be able to give machine the access to data and let them learn from themselves.', 'start': 121.656, 'duration': 5.822}, {'end': 132.781, 'text': "It's a subset of artificial intelligence that deals with the extraction of pattern from data set.", 'start': 128.139, 'duration': 4.642}, {'end': 139.724, 'text': 'This means that the machine can not only find the rules for optimal behavior, but also can adapt to the changes in the world.', 'start': 133.341, 'duration': 6.383}], 'summary': "Machine learning is a subset of ai, enabling machines to learn and make data-driven decisions, with examples like tesla's self-driving car and apple siri.", 'duration': 135.498, 'max_score': 4.226, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/Pj0neYUp9Tc/pics/Pj0neYUp9Tc4226.jpg'}, {'end': 177.57, 'src': 'embed', 'start': 155.639, 'weight': 9, 'content': [{'end': 167.644, 'text': 'deep learning is a subset of machine learning where similar machine learning algorithm are used to train deep neural network so as to achieve better accuracy in those cases where former was not performing up to the mark right?', 'start': 155.639, 'duration': 12.005}, {'end': 173.125, 'text': 'I hope now you understood that machine learning, AI and deep learning all three are different.', 'start': 168.519, 'duration': 4.606}, {'end': 174.686, 'text': 'Okay, moving on ahead.', 'start': 173.705, 'duration': 0.981}, {'end': 177.57, 'text': "Let's see in general how a machine learning work.", 'start': 175.167, 'duration': 2.403}], 'summary': 'Deep learning uses machine learning algorithms to train deep neural networks for improved accuracy. it is distinct from machine learning and ai.', 'duration': 21.931, 'max_score': 155.639, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/Pj0neYUp9Tc/pics/Pj0neYUp9Tc155639.jpg'}, {'end': 204.065, 'src': 'heatmap', 'start': 155.639, 'weight': 0.749, 'content': [{'end': 167.644, 'text': 'deep learning is a subset of machine learning where similar machine learning algorithm are used to train deep neural network so as to achieve better accuracy in those cases where former was not performing up to the mark right?', 'start': 155.639, 'duration': 12.005}, {'end': 173.125, 'text': 'I hope now you understood that machine learning, AI and deep learning all three are different.', 'start': 168.519, 'duration': 4.606}, {'end': 174.686, 'text': 'Okay, moving on ahead.', 'start': 173.705, 'duration': 0.981}, {'end': 177.57, 'text': "Let's see in general how a machine learning work.", 'start': 175.167, 'duration': 2.403}, {'end': 184.598, 'text': 'One of the approaches is where the machine learning algorithm is trained using a label or unlabeled training data set to produce a model.', 'start': 178.331, 'duration': 6.267}, {'end': 189.938, 'text': 'New input data is introduced to the machine learning algorithm and it make prediction based on the model.', 'start': 185.336, 'duration': 4.602}, {'end': 197.121, 'text': 'The prediction is evaluated for accuracy and if the accuracy is acceptable, the machine learning algorithm is deployed.', 'start': 190.458, 'duration': 6.663}, {'end': 204.065, 'text': 'Now if the accuracy is not acceptable, the machine learning algorithm is trained again and again with an augmented training data set.', 'start': 197.662, 'duration': 6.403}], 'summary': 'Deep learning improves accuracy in machine learning; model trained, data predicted, accuracy evaluated, and algorithm deployed if acceptable.', 'duration': 48.426, 'max_score': 155.639, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/Pj0neYUp9Tc/pics/Pj0neYUp9Tc155639.jpg'}], 'start': 4.226, 'title': 'Machine learning fundamentals', 'summary': 'Introduces machine learning and its applications, explains the differences between ai, machine learning, and deep learning, and provides an overview of machine learning and deep learning, including their working, subcategories, and applications in various domains.', 'chapters': [{'end': 82.389, 'start': 4.226, 'title': 'Introduction to machine learning', 'summary': "Introduces the concept of machine learning as a subfield of artificial intelligence that enables computers to learn and make data-driven decisions, citing examples such as tesla's self-driving car and apple's siri.", 'duration': 78.163, 'highlights': ['Machine learning is a subfield of artificial intelligence focused on designing systems that can learn from and make decisions based on data. Machine learning is a subfield of artificial intelligence that focuses on the design of system that can learn from and make decisions and predictions based on the experience, which is data.', "Examples of machine learning implementations include Tesla's self-driving car and Apple's Siri. You can see various examples or implementation of machine learning around us, such as Tesla's self-driving car, Apple Siri, Sofia, AI robot, and many more.", 'Machine learning enables computers to act and make data-driven decisions rather than being explicitly programmed to carry out tasks. In the case of machines, machine learning enables computer to act and make data-driven decisions rather than being explicitly programmed to carry out a certain task.']}, {'end': 139.724, 'start': 82.941, 'title': 'Ai, machine learning, and deep learning', 'summary': 'Explains the differences between artificial intelligence, machine learning, and deep learning, highlighting that artificial intelligence is a broader concept, while machine learning is a subset of ai that allows machines to learn from data.', 'duration': 56.783, 'highlights': ['Artificial intelligence is a broader concept of machines being able to carry out tasks in a smarter way, covering anything which enables the computer to behave like humans.', 'Machine learning is a subset of artificial intelligence, based on the idea that machines should be able to access data and learn from themselves to extract patterns from data sets and adapt to changes in the world.', 'The famous Turing test is used to determine whether a computer is capable of thinking like a human being, exemplified by interactions with virtual assistants like Siri on smartphones.']}, {'end': 231.411, 'start': 140.333, 'title': 'Machine learning & deep learning overview', 'summary': 'Discusses the advancements in machine learning and deep learning, highlighting their ability to scale up to massive data volumes and the distinction between the two. it also covers the general working of machine learning, including its training process, model prediction, and deployment. additionally, it introduces the subcategorization of machine learning into supervised learning, unsupervised learning, and reinforcement learning, and their applications in various domains.', 'duration': 91.078, 'highlights': ['Machine learning algorithms can now scale up to massive data volumes, thanks to advances in computer science and parallel computing.', 'Deep learning is a subset of machine learning that uses deep neural networks to achieve better accuracy in cases where traditional machine learning algorithms fall short.', 'The general working of machine learning involves training the algorithm with labeled or unlabeled data, introducing new input data, evaluating predictions for accuracy, and deploying the algorithm based on the accuracy.', 'Machine learning is subcategorized into supervised learning, unsupervised learning, and reinforcement learning, each with distinct working principles and applications in domains like banking, healthcare, and retail.']}], 'duration': 227.185, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/Pj0neYUp9Tc/pics/Pj0neYUp9Tc4226.jpg', 'highlights': ['Machine learning is a subfield of artificial intelligence focused on designing systems that can learn from and make decisions based on data.', 'Machine learning enables computers to act and make data-driven decisions rather than being explicitly programmed to carry out tasks.', "Examples of machine learning implementations include Tesla's self-driving car and Apple's Siri.", 'Artificial intelligence is a broader concept of machines being able to carry out tasks in a smarter way, covering anything which enables the computer to behave like humans.', 'Machine learning is a subset of artificial intelligence, based on the idea that machines should be able to access data and learn from themselves to extract patterns from data sets and adapt to changes in the world.', 'The famous Turing test is used to determine whether a computer is capable of thinking like a human being, exemplified by interactions with virtual assistants like Siri on smartphones.', 'Machine learning algorithms can now scale up to massive data volumes, thanks to advances in computer science and parallel computing.', 'Deep learning is a subset of machine learning that uses deep neural networks to achieve better accuracy in cases where traditional machine learning algorithms fall short.', 'The general working of machine learning involves training the algorithm with labeled or unlabeled data, introducing new input data, evaluating predictions for accuracy, and deploying the algorithm based on the accuracy.', 'Machine learning is subcategorized into supervised learning, unsupervised learning, and reinforcement learning, each with distinct working principles and applications in domains like banking, healthcare, and retail.']}, {'end': 532.663, 'segs': [{'end': 259.724, 'src': 'embed', 'start': 231.992, 'weight': 1, 'content': [{'end': 238.575, 'text': "So starting with supervised learning, what is it? So let's see a mathematical definition of supervised learning.", 'start': 231.992, 'duration': 6.583}, {'end': 249.081, 'text': 'Supervised learning is where you have input variables X and an output variable Y and you use an algorithm to learn the mapping function from the input to the output.', 'start': 239.278, 'duration': 9.803}, {'end': 250.441, 'text': 'that is, y equal FX.', 'start': 249.081, 'duration': 1.36}, {'end': 253.342, 'text': 'The goal is to approximate the mapping function.', 'start': 251.062, 'duration': 2.28}, {'end': 259.724, 'text': 'So well that whenever you have a new input data X, you could predict the output variable that is Y for that data.', 'start': 253.402, 'duration': 6.322}], 'summary': 'Supervised learning involves learning a mapping function from input variables x to output variable y, aiming to predict y for new input data.', 'duration': 27.732, 'max_score': 231.992, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/Pj0neYUp9Tc/pics/Pj0neYUp9Tc231992.jpg'}, {'end': 372.869, 'src': 'embed', 'start': 332.55, 'weight': 0, 'content': [{'end': 336.593, 'text': 'It can easily predict the correct output of a never seen input in this slide.', 'start': 332.55, 'duration': 4.043}, {'end': 343.819, 'text': 'You can see that we are giving an image of a green apple to the machine and the machine can easily identify it as, yes,', 'start': 336.633, 'duration': 7.186}, {'end': 346.461, 'text': 'it is an apple and it is giving the correct result right?', 'start': 343.819, 'duration': 2.642}, {'end': 348.663, 'text': 'Let me make things more clearer to you.', 'start': 346.901, 'duration': 1.762}, {'end': 350.584, 'text': "Let's discuss another example of it.", 'start': 348.903, 'duration': 1.681}, {'end': 352.165, 'text': 'So, in this slide,', 'start': 351.205, 'duration': 0.96}, {'end': 359.291, 'text': 'the image shows an example of a supervised learning process used to produce a model which is capable of recognizing the ducks in the image.', 'start': 352.165, 'duration': 7.126}, {'end': 364.106, 'text': 'The training data set is composed of label picture of ducts and non-ducks.', 'start': 359.904, 'duration': 4.202}, {'end': 372.869, 'text': 'the result of supervised learning process is a predictive model which is capable of associating a label duck or not duck to the new image presented to the model.', 'start': 364.106, 'duration': 8.763}], 'summary': 'Supervised learning can predict new inputs accurately, as seen with apple and duck recognition examples.', 'duration': 40.319, 'max_score': 332.55, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/Pj0neYUp9Tc/pics/Pj0neYUp9Tc332550.jpg'}, {'end': 414.135, 'src': 'embed', 'start': 389.267, 'weight': 4, 'content': [{'end': 397.77, 'text': 'Well, it is called as supervised learning because the process of an algorithm learning from the training data set can be thought of as a teacher supervising the learning process.', 'start': 389.267, 'duration': 8.503}, {'end': 406.092, 'text': 'We know the correct answers the algorithm iteratively makes while predicting on the training data and is corrected by the teacher.', 'start': 398.49, 'duration': 7.602}, {'end': 410.154, 'text': 'the learning stops when the algorithm achieves an acceptable level of performance.', 'start': 406.092, 'duration': 4.062}, {'end': 414.135, 'text': "Now, let's move on and see some of the popular supervised learning algorithm.", 'start': 411.014, 'duration': 3.121}], 'summary': 'Supervised learning uses training data with known answers to teach algorithms until they achieve acceptable performance.', 'duration': 24.868, 'max_score': 389.267, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/Pj0neYUp9Tc/pics/Pj0neYUp9Tc389267.jpg'}], 'start': 231.992, 'title': 'Supervised learning in machine learning', 'summary': 'Discusses the definition of supervised learning and its goal to learn the mapping function, along with its application in machine learning, including popular algorithms and use cases in sectors like banking and healthcare.', 'chapters': [{'end': 270.922, 'start': 231.992, 'title': 'Supervised learning definition', 'summary': "Explains the mathematical definition of supervised learning, emphasizing the algorithm's goal to learn the mapping function from input variables to output variables in order to predict new output variables for given input data.", 'duration': 38.93, 'highlights': ['Supervised learning is where you have input variables X and an output variable Y and you use an algorithm to learn the mapping function from the input to the output with the goal to approximate the mapping function.', "The algorithm's goal is to learn the mapping function from the input to the output so that whenever you have a new input data X, you could predict the output variable Y for that data.", 'The chapter simplifies the definition of supervised learning as a machine learning method.']}, {'end': 532.663, 'start': 270.922, 'title': 'Supervised learning in machine learning', 'summary': 'Introduces supervised learning in machine learning, explaining how an algorithm learns from training data to predict correct outputs for new inputs, and provides examples of popular algorithms and use cases, such as cortana and weather app, in various sectors like banking and healthcare.', 'duration': 261.741, 'highlights': ['Supervised learning enables an algorithm to predict correct outputs for new inputs by learning from training data, with examples like image recognition and model production. The algorithm learns from training data to predict the correct output of a never seen input, such as identifying an image of a green apple as an apple, and producing a model capable of recognizing ducks in an image.', 'Popular supervised learning algorithms include linear regression, random forest, and support vector machines, with plans to discuss them in the next video. Linear regression, random forest, and support vector machines are mentioned as popular supervised learning algorithms, with a promise to discuss them in a future video.', 'Use cases of supervised learning span across various sectors, including speech automation, weather app predictions, biometric attendance, banking, healthcare, and retail. Supervised learning finds applications in speech automation, weather app predictions, biometric attendance, banking (credit worthiness prediction), healthcare (patient readmission rate prediction), and retail (product analysis).']}], 'duration': 300.671, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/Pj0neYUp9Tc/pics/Pj0neYUp9Tc231992.jpg', 'highlights': ['Supervised learning is where you have input variables X and an output variable Y and you use an algorithm to learn the mapping function from the input to the output with the goal to approximate the mapping function.', "The algorithm's goal is to learn the mapping function from the input to the output so that whenever you have a new input data X, you could predict the output variable Y for that data.", 'Supervised learning enables an algorithm to predict correct outputs for new inputs by learning from training data, with examples like image recognition and model production.', 'Popular supervised learning algorithms include linear regression, random forest, and support vector machines, with plans to discuss them in the next video.', 'Use cases of supervised learning span across various sectors, including speech automation, weather app predictions, biometric attendance, banking, healthcare, and retail.']}, {'end': 1039.942, 'segs': [{'end': 731.892, 'src': 'embed', 'start': 694.392, 'weight': 3, 'content': [{'end': 697.673, 'text': 'Now why this learning is different from supervised learning.', 'start': 694.392, 'duration': 3.281}, {'end': 704.336, 'text': "since you didn't use any past or prior knowledge about the people, you kept on classifying them on the go as they kept on coming.", 'start': 697.673, 'duration': 6.663}, {'end': 705.856, 'text': 'you kept on classifying them at.', 'start': 704.336, 'duration': 1.52}, {'end': 710.118, 'text': 'this category of people belong to this group, this category of people belong to that group, and so on.', 'start': 705.856, 'duration': 4.262}, {'end': 712.559, 'text': "Okay, let's see one more example.", 'start': 710.638, 'duration': 1.921}, {'end': 718.563, 'text': "Let's suppose you have never seen a football match before and by chance you watch a video on the internet.", 'start': 713.239, 'duration': 5.324}, {'end': 726.008, 'text': 'now you can easily classify the players on the basis of different criterion like player wearing the same kind of Jersey are in one class,', 'start': 718.563, 'duration': 7.445}, {'end': 731.892, 'text': 'player wearing different kind of Jersey, are in different class, or you can classify them on the basis of their playing style,', 'start': 726.008, 'duration': 5.884}], 'summary': 'Unsupervised learning involves real-time classification without prior knowledge, as demonstrated by classifying people and football players based on observable characteristics.', 'duration': 37.5, 'max_score': 694.392, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/Pj0neYUp9Tc/pics/Pj0neYUp9Tc694392.jpg'}, {'end': 776.849, 'src': 'embed', 'start': 750.874, 'weight': 0, 'content': [{'end': 757.058, 'text': 'So, in banking sector, it is used to segment customers by behavioral characteristic, by surveying prospects,', 'start': 750.874, 'duration': 6.184}, {'end': 760.36, 'text': 'and customers to develop multiple segments using clustering.', 'start': 757.058, 'duration': 3.302}, {'end': 761.917, 'text': 'In healthcare sector.', 'start': 761.016, 'duration': 0.901}, {'end': 765.88, 'text': 'It is used to categorize the MRA data by normal or abnormal images.', 'start': 762.037, 'duration': 3.843}, {'end': 773.206, 'text': 'It uses deep learning techniques to build a model that learns from different features of images to recognize a different pattern.', 'start': 766.501, 'duration': 6.705}, {'end': 776.849, 'text': 'Next is the retail sector in retail sector.', 'start': 773.987, 'duration': 2.862}], 'summary': "In banking, segmentation is used for customer behavior; in healthcare, it categorizes mra data; and in retail, it's applied for unknown uses.", 'duration': 25.975, 'max_score': 750.874, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/Pj0neYUp9Tc/pics/Pj0neYUp9Tc750874.jpg'}, {'end': 842.84, 'src': 'heatmap', 'start': 802.114, 'weight': 0.787, 'content': [{'end': 803.655, 'text': 'So what is reinforcement learning??', 'start': 802.114, 'duration': 1.541}, {'end': 815.298, 'text': 'Well, reinforcement learning is a type of machine learning algorithm which allows software agents and machine to automatically determine the ideal behavior within a specific context to maximize its performance.', 'start': 804.195, 'duration': 11.103}, {'end': 816.766, 'text': 'The reinforcement.', 'start': 815.925, 'duration': 0.841}, {'end': 821.769, 'text': 'learning is about interaction between two elements the environment and the learning agent.', 'start': 816.766, 'duration': 5.003}, {'end': 826.512, 'text': 'the learning agent leverages to mechanism, namely exploration and exploitation.', 'start': 821.769, 'duration': 4.743}, {'end': 829.748, 'text': 'When learning agent acts on trial and error basis.', 'start': 827.265, 'duration': 2.483}, {'end': 835.093, 'text': 'It is termed as exploration and when it acts based on the knowledge gained from the environment.', 'start': 830.128, 'duration': 4.965}, {'end': 842.84, 'text': 'It is referred to as exploitation, and this environment rewards the agent for correct actions, which is reinforcement signal.', 'start': 835.273, 'duration': 7.567}], 'summary': 'Reinforcement learning maximizes performance by interaction between agent and environment.', 'duration': 40.726, 'max_score': 802.114, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/Pj0neYUp9Tc/pics/Pj0neYUp9Tc802114.jpg'}, {'end': 886.888, 'src': 'embed', 'start': 858.442, 'weight': 2, 'content': [{'end': 863.725, 'text': 'if it makes correct decision, it get rewards point for it and in case of wrong, it gets a penalty for that.', 'start': 858.442, 'duration': 5.283}, {'end': 865.51, 'text': 'Once the training is done.', 'start': 864.429, 'duration': 1.081}, {'end': 869.413, 'text': 'Now the machine can easily identify which one of them is an apple.', 'start': 865.83, 'duration': 3.583}, {'end': 871.295, 'text': "Let's see an example here.", 'start': 869.954, 'duration': 1.341}, {'end': 877.04, 'text': 'We can see that we have an agent who has to judge from the environment to find out which of the two is a duck.', 'start': 871.315, 'duration': 5.725}, {'end': 882.664, 'text': 'The first task he did is to observe the environment next to select some action using some policy.', 'start': 877.36, 'duration': 5.304}, {'end': 886.888, 'text': 'It seems that the machine has made a wrong decision by choosing a bunny as a duck.', 'start': 883.185, 'duration': 3.703}], 'summary': 'Machine learns to identify objects, receives rewards for correct decisions, and penalized for wrong decisions.', 'duration': 28.446, 'max_score': 858.442, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/Pj0neYUp9Tc/pics/Pj0neYUp9Tc858442.jpg'}, {'end': 925.863, 'src': 'embed', 'start': 899.692, 'weight': 1, 'content': [{'end': 903.614, 'text': 'from the next time, machine will know that bunny is not a duck.', 'start': 899.692, 'duration': 3.922}, {'end': 906.876, 'text': "Let's see some of the use cases of reinforcement learning.", 'start': 904.294, 'duration': 2.582}, {'end': 915.46, 'text': "But before that, let's see how Pavlo trained his dog using reinforcement learning or how he applied the reinforcement method to train his dog.", 'start': 907.496, 'duration': 7.964}, {'end': 925.863, 'text': 'Pavlo integrated learning in four stages initially Pavlo gave meat to his dog and in response to the meat the dog started salivating next what he did.', 'start': 916.252, 'duration': 9.611}], 'summary': 'Reinforcement learning applied to dog training in four stages', 'duration': 26.171, 'max_score': 899.692, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/Pj0neYUp9Tc/pics/Pj0neYUp9Tc899692.jpg'}], 'start': 533.163, 'title': 'Unsupervised and reinforcement learning in ml', 'summary': 'Covers unsupervised learning basics, including its applications in banking, healthcare, and retail, and popular algorithms. it also introduces reinforcement learning, explaining its components, mechanisms, and applications, with examples and use cases in various sectors.', 'chapters': [{'end': 796.413, 'start': 533.163, 'title': 'Unsupervised learning basics', 'summary': 'Explains unsupervised learning, its main goal, examples, and its applications in banking, healthcare, and retail. it also mentions some popular unsupervised learning algorithms.', 'duration': 263.25, 'highlights': ['Unsupervised learning aims to identify the underlying structure or distribution in the data. The goal of unsupervised learning is to model the underlying structure or distribution in the data without any corresponding output variable.', 'Clustering is an example of a machine learning task that applies unsupervised learning. Clustering is an example of a machine learning task that applies unsupervised learning, where similar data instances are grouped together to identify clusters of data.', 'Unsupervised learning is used in the banking sector to segment customers by behavioral characteristics. In the banking sector, unsupervised learning is used to segment customers by behavioral characteristics and develop multiple segments using clustering.', 'In the healthcare sector, unsupervised learning is used to categorize MRI data as normal or abnormal images. In the healthcare sector, unsupervised learning is used to categorize MRI data as normal or abnormal images using deep learning techniques.', 'In the retail sector, unsupervised learning is used to recommend products to customers based on their past purchases. In the retail sector, unsupervised learning is used to recommend products to customers based on their past purchases by building a collaborative filtering model.']}, {'end': 1039.942, 'start': 797.153, 'title': 'Reinforcement learning in ml', 'summary': "Introduces reinforcement learning in machine learning, explaining its components, mechanisms, and applications, including examples of pavlov's dog and use cases in banking, healthcare, and retail sectors.", 'duration': 242.789, 'highlights': ['Reinforcement learning involves interaction between the environment and the learning agent, leveraging mechanisms of exploration and exploitation. The reinforcement learning process involves interaction between the environment and the learning agent, utilizing mechanisms of exploration (trial and error) and exploitation (using gained knowledge).', 'Reinforcement learning is applied in banking to create a next best offer model for call centers, in healthcare to allocate medical resources for ER cases, and in retail to reduce excess stock with dynamic pricing. Reinforcement learning is utilized in banking to develop a predictive model for call centers, in healthcare to allocate medical resources for ER cases, and in retail to adjust pricing based on customer response.', "Pavlov's dog was trained using reinforcement learning, demonstrating the concept of conditioning through rewards and stimuli. Pavlov applied reinforcement learning in four stages to train his dog, demonstrating conditioning through rewards and stimuli, leading to a learned response."]}], 'duration': 506.779, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/Pj0neYUp9Tc/pics/Pj0neYUp9Tc533163.jpg', 'highlights': ['Reinforcement learning involves interaction between the environment and the learning agent, leveraging mechanisms of exploration and exploitation.', 'Reinforcement learning is applied in banking to create a next best offer model for call centers, in healthcare to allocate medical resources for ER cases, and in retail to reduce excess stock with dynamic pricing.', "Pavlov's dog was trained using reinforcement learning, demonstrating the concept of conditioning through rewards and stimuli.", 'Unsupervised learning is used in the banking sector to segment customers by behavioral characteristics.', 'In the healthcare sector, unsupervised learning is used to categorize MRI data as normal or abnormal images.', 'In the retail sector, unsupervised learning is used to recommend products to customers based on their past purchases.']}], 'highlights': ['Machine learning enables computers to act and make data-driven decisions rather than being explicitly programmed to carry out tasks.', 'Supervised learning is where you have input variables X and an output variable Y and you use an algorithm to learn the mapping function from the input to the output with the goal to approximate the mapping function.', 'Reinforcement learning involves interaction between the environment and the learning agent, leveraging mechanisms of exploration and exploitation.']}