title
Jupyter Notebook Tutorial | Introduction To Jupyter Notebook | Python Jupyter Notebook | Simplilearn

description
🔥Professional Certificate Course In AI And Machine Learning by IIT Kanpur (India Only): https://www.simplilearn.com/iitk-professional-certificate-course-ai-machine-learning?utm_campaign=23AugustTubebuddyExpPCPAIandML&utm_medium=DescriptionFF&utm_source=youtube 🔥AI Engineer Masters Program (Discount Code - YTBE15): https://www.simplilearn.com/masters-in-artificial-intelligence?utm_campaign=SCE-AIMasters&utm_medium=DescriptionFF&utm_source=youtube 🔥AI & Machine Learning Bootcamp(US Only): https://www.simplilearn.com/ai-machine-learning-bootcamp?utm_campaign=Python-3C9E2yPBw7s&utm_medium=Descriptionff&utm_source=youtube 🔥 Purdue Post Graduate Program In AI And Machine Learning: https://www.simplilearn.com/pgp-ai-machine-learning-certification-training-course?utm_campaign=Python-3C9E2yPBw7s&utm_medium=Descriptionff&utm_source=youtube Below topics are explained in this Jupyter notebook tutorial: 1. What is Jupyter notebook? 2. How to install Jupyter notebook? 3. Pre-requisites to install Jupyter notebook 4. Demo - Jupyter notebook To learn more about Python Programming, subscribe to our YouTube channel: https://www.youtube.com/user/Simplilearn?sub_confirmation=1 Watch more videos on Python Training: https://www.youtube.com/watch?v=syH5OneJb-U&index=2&list=PLEiEAq2VkUUKoW1o-A-VEmkoGKSC26i_I #pythontutorial #pythonjupyternotebook #pythonprogrammingforbeginners #pythontraining #pythontutorialforbeginners #jupyternotebookinstall #pythonsimplilearn #simplilearn ➡️ About Post Graduate Program In AI And Machine Learning This AI ML course is designed to enhance your career in AI and ML by demystifying concepts like machine learning, deep learning, NLP, computer vision, reinforcement learning, and more. You'll also have access to 4 live sessions, led by industry experts, covering the latest advancements in AI such as generative modeling, ChatGPT, OpenAI, and chatbots. ✅ Key Features - Post Graduate Program certificate and Alumni Association membership - Exclusive hackathons and Ask me Anything sessions by IBM - 3 Capstones and 25+ Projects with industry data sets from Twitter, Uber, Mercedes Benz, and many more - Master Classes delivered by Purdue faculty and IBM experts - Simplilearn's JobAssist helps you get noticed by top hiring companies - Gain access to 4 live online sessions on latest AI trends such as ChatGPT, generative AI, explainable AI, and more - Learn about the applications of ChatGPT, OpenAI, Dall-E, Midjourney & other prominent tools ✅ Skills Covered - ChatGPT - Generative AI - Explainable AI - Generative Modeling - Statistics - Python - Supervised Learning - Unsupervised Learning - NLP - Neural Networks - Computer Vision - And Many More… Learn more at: https://www.simplilearn.com/mobile-and-software-development/python-development-training?utm_campaign=Jupyter-Notebook-Tutorial-3C9E2yPBw7s&utm_medium=Tutorials&utm_source=youtube 🔥 Enrol for FREE Six Sigma Course & Get your Completion Certificate: https://www.simplilearn.com/skillup-free-online-courses?utm_campaign=Python&utm_medium=Description&utm_source=youtube 🔥🔥 Interested in Attending Live Classes? Call Us: IN - 18002127688 / US - +18445327688

detail
{'title': 'Jupyter Notebook Tutorial | Introduction To Jupyter Notebook | Python Jupyter Notebook | Simplilearn', 'heatmap': [{'end': 756.385, 'start': 730.646, 'weight': 1}], 'summary': 'This tutorial series covers installing jupyter notebook using anaconda, managing environments, data visualization, and utilizing anaconda functionalities. it includes creating environments, running code cells, managing kernels, and accessing tools such as jupyter lab and rstudio.', 'chapters': [{'end': 200.219, 'segs': [{'end': 73.628, 'src': 'embed', 'start': 28.586, 'weight': 0, 'content': [{'end': 34.19, 'text': 'you can click on the install button and then you can run the prerequisites Python and downloads here.', 'start': 28.586, 'duration': 5.604}, {'end': 35.652, 'text': 'And you can see the setup on this.', 'start': 34.211, 'duration': 1.441}, {'end': 42.114, 'text': "And you'll see the very first thing they suggest is that you install Jupyter using the Anaconda.", 'start': 36.152, 'duration': 5.962}, {'end': 48.496, 'text': "So we have Jupyter Notebook, and then we have the Anaconda setup, and that's www.anaconda.com.", 'start': 42.474, 'duration': 6.022}, {'end': 50.237, 'text': 'You just go up to the downloads.', 'start': 48.736, 'duration': 1.501}, {'end': 59.4, 'text': "Once you're under the downloads, you'll see in the Anaconda that they have it set for version 3.7 or 2.7.", 'start': 50.877, 'duration': 8.523}, {'end': 67.283, 'text': "I generally work in the newer version, although I did have to reset my Anaconda to 3.6 for working with Google's TensorFlow,", 'start': 59.4, 'duration': 7.883}, {'end': 69.185, 'text': 'which you can do very easily in Anaconda.', 'start': 67.283, 'duration': 1.902}, {'end': 73.628, 'text': 'I remember the first time someone showed me Jupyter Notebook in Anaconda.', 'start': 69.265, 'duration': 4.363}], 'summary': 'Install jupyter using anaconda, version 3.7 or 2.7, easily switch for tensorflow in 3.6.', 'duration': 45.042, 'max_score': 28.586, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/3C9E2yPBw7s/pics/3C9E2yPBw7s28586.jpg'}, {'end': 135.044, 'src': 'embed', 'start': 91.862, 'weight': 2, 'content': [{'end': 94.284, 'text': 'Let me just flip back on over here for the Jupyter symbol.', 'start': 91.862, 'duration': 2.422}, {'end': 103.029, 'text': 'And then Anaconda creates environments, so it makes it very easy to create a Python 3.7 environment with the different modules installed.', 'start': 94.424, 'duration': 8.605}, {'end': 110.314, 'text': "So if you're working with a referenced Google TensorFlow, had a little troubles with that and had to go to Python 3.6, you can easily do that.", 'start': 103.069, 'duration': 7.245}, {'end': 113.436, 'text': 'You can create an environment for Python 3.6.', 'start': 110.374, 'duration': 3.062}, {'end': 115.157, 'text': "And that's all through the Anaconda.", 'start': 113.436, 'duration': 1.721}, {'end': 119.998, 'text': "So once you've installed this, there's a couple ways to get to your Jupyter Notebook.", 'start': 115.337, 'duration': 4.661}, {'end': 123.3, 'text': "So you'll go ahead and just download and run the Anaconda install.", 'start': 120.119, 'duration': 3.181}, {'end': 128.08, 'text': 'And then in this case, I go under my windows and I actually have Anaconda 64-bit.', 'start': 123.54, 'duration': 4.54}, {'end': 130.442, 'text': 'And we can go to Anaconda.', 'start': 128.521, 'duration': 1.921}, {'end': 131.543, 'text': "There's Jupyter Notebook.", 'start': 130.762, 'duration': 0.781}, {'end': 133.183, 'text': 'You can directly access it that way.', 'start': 131.583, 'duration': 1.6}, {'end': 135.044, 'text': 'You can do the Anaconda prompt.', 'start': 133.383, 'duration': 1.661}], 'summary': 'Anaconda simplifies creating python environments and accessing jupyter notebook, allowing easy switching between versions.', 'duration': 43.182, 'max_score': 91.862, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/3C9E2yPBw7s/pics/3C9E2yPBw7s91862.jpg'}], 'start': 3.433, 'title': 'Installing jupyter notebook with anaconda', 'summary': 'Covers the process of installing jupyter notebook using anaconda, including the version options, creating environments, and accessing jupyter notebook through anaconda navigator and anaconda prompt.', 'chapters': [{'end': 200.219, 'start': 3.433, 'title': 'Installing jupyter notebook with anaconda', 'summary': 'Covers the process of installing jupyter notebook using anaconda, including the version options, creating environments, and accessing jupyter notebook through anaconda navigator and anaconda prompt.', 'duration': 196.786, 'highlights': ['The chapter explains the process of installing Jupyter Notebook using Anaconda, including the recommendation to use Anaconda for installation.', "It discusses the version options for Anaconda, specifically version 3.7 and 2.7, and the flexibility to work with different Python versions, such as 3.6 for Google's TensorFlow.", 'It highlights the ease of creating Python environments with Anaconda, allowing for the installation of different modules and the ability to work with different Python versions, such as Python 3.6 for specific projects.', 'The chapter demonstrates multiple ways to access Jupyter Notebook after installation, including using Anaconda Navigator and Anaconda Prompt, as well as directly accessing it through the Anaconda installation.']}], 'duration': 196.786, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/3C9E2yPBw7s/pics/3C9E2yPBw7s3433.jpg', 'highlights': ['The chapter explains the process of installing Jupyter Notebook using Anaconda, including the recommendation to use Anaconda for installation.', "It discusses the version options for Anaconda, specifically version 3.7 and 2.7, and the flexibility to work with different Python versions, such as 3.6 for Google's TensorFlow.", 'The chapter demonstrates multiple ways to access Jupyter Notebook after installation, including using Anaconda Navigator and Anaconda Prompt, as well as directly accessing it through the Anaconda installation.', 'It highlights the ease of creating Python environments with Anaconda, allowing for the installation of different modules and the ability to work with different Python versions, such as Python 3.6 for specific projects.']}, {'end': 665.718, 'segs': [{'end': 277.442, 'src': 'embed', 'start': 239.475, 'weight': 0, 'content': [{'end': 242.137, 'text': "When you're in an environment, don't mix and match the two.", 'start': 239.475, 'duration': 2.662}, {'end': 248.22, 'text': 'Stick with conda or stick with pip because you can run into problems with imports and reliance and stuff like that.', 'start': 242.397, 'duration': 5.823}, {'end': 252.403, 'text': "So we'll go ahead and go under data science because that's what I enjoy doing, data science.", 'start': 248.56, 'duration': 3.843}, {'end': 258.607, 'text': "So when I go back to my home menu, You'll see my data science opens up and I have my Jupyter Notebook first thing.", 'start': 252.723, 'duration': 5.884}, {'end': 260.028, 'text': "And there's a lot of tools.", 'start': 258.906, 'duration': 1.122}, {'end': 262.65, 'text': 'You can open up RStudio from in here.', 'start': 260.048, 'duration': 2.602}, {'end': 265.973, 'text': "I've never really used Spyder that much, but Spyder is another Python editor.", 'start': 262.83, 'duration': 3.143}, {'end': 268.455, 'text': "There's the Jupyter Lab, VS Coding.", 'start': 266.313, 'duration': 2.142}, {'end': 269.876, 'text': "So there's a lot of steps in here.", 'start': 268.695, 'duration': 1.181}, {'end': 271.297, 'text': "There's even stuff you can add in.", 'start': 269.896, 'duration': 1.401}, {'end': 275.901, 'text': 'Mostly I use Jupyter Notebook and then occasionally I use RStudio.', 'start': 271.637, 'duration': 4.264}, {'end': 277.442, 'text': 'So I try to wrap everything in here.', 'start': 275.961, 'duration': 1.481}], 'summary': 'Stick with either conda or pip to avoid import problems. prefers jupyter notebook and occasionally uses rstudio for data science.', 'duration': 37.967, 'max_score': 239.475, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/3C9E2yPBw7s/pics/3C9E2yPBw7s239475.jpg'}, {'end': 328.373, 'src': 'embed', 'start': 297.395, 'weight': 2, 'content': [{'end': 300.257, 'text': "i'm now in jupyter notebook, just like we did the other way.", 'start': 297.395, 'duration': 2.862}, {'end': 302.478, 'text': 'so we did it two different ways to get in here.', 'start': 300.257, 'duration': 2.221}, {'end': 306.32, 'text': "this is i've set this to my data science setup.", 'start': 302.478, 'duration': 3.842}, {'end': 308.341, 'text': "you'll see down here i have folders.", 'start': 306.32, 'duration': 2.021}, {'end': 309.742, 'text': "it's actually on my d drive.", 'start': 308.341, 'duration': 1.401}, {'end': 313.024, 'text': 'i pointed this to my d drives because where i keep everything and i can go under,', 'start': 309.742, 'duration': 3.282}, {'end': 316.386, 'text': 'simply learn and you can see we have different tutorials and different things.', 'start': 313.024, 'duration': 3.362}, {'end': 319.147, 'text': "we've done in here over the years, actually over the last year.", 'start': 316.386, 'duration': 2.761}, {'end': 323.03, 'text': 'since this is a fairly new computer, this is over the last couple months, I think my oldest one here, yeah.', 'start': 319.147, 'duration': 3.883}, {'end': 328.373, 'text': "Oh, I do have something from five months ago, but that was brought up, brought it in from earlier, so it's about two months old on my computer.", 'start': 323.21, 'duration': 5.163}], 'summary': 'Using jupyter notebook, accessing data stored in d drive, with tutorials and projects from the last year and couple of months.', 'duration': 30.978, 'max_score': 297.395, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/3C9E2yPBw7s/pics/3C9E2yPBw7s297395.jpg'}, {'end': 448.924, 'src': 'embed', 'start': 420.18, 'weight': 3, 'content': [{'end': 421.44, 'text': "And it's got an open kernel.", 'start': 420.18, 'duration': 1.26}, {'end': 425.002, 'text': 'Now kernel, it opens up a kernel to execute the program in.', 'start': 421.6, 'duration': 3.402}, {'end': 429.705, 'text': "And when we're looking at this, it's important to know that it's only setting up one kernel.", 'start': 425.463, 'duration': 4.242}, {'end': 435.508, 'text': 'So everything in your Jupyter Notebook is going to work great except for multi-processing.', 'start': 430.245, 'duration': 5.263}, {'end': 440.851, 'text': "Even multi-threading works fine in Jupyter Notebook, but if you get into multi-processing, you'll start seeing some problems,", 'start': 435.829, 'duration': 5.022}, {'end': 443.233, 'text': "because it's only opening up one kernel to run it in here.", 'start': 440.851, 'duration': 2.382}, {'end': 447.483, 'text': 'And if we go under a kernel, you can see how we can restart it.', 'start': 443.7, 'duration': 3.783}, {'end': 448.924, 'text': 'Make sure you want to restart it.', 'start': 447.503, 'duration': 1.421}], 'summary': 'Jupyter notebook supports only one kernel, leading to issues with multi-processing.', 'duration': 28.744, 'max_score': 420.18, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/3C9E2yPBw7s/pics/3C9E2yPBw7s420180.jpg'}, {'end': 656.107, 'src': 'embed', 'start': 627.071, 'weight': 5, 'content': [{'end': 632.354, 'text': 'This inline editing and output makes us great for doing presentations.', 'start': 627.071, 'duration': 5.283}, {'end': 641.117, 'text': 'The first time I did this, we were doing a data science predicting when the huge blowers on the sewage plant go out, these huge aerators.', 'start': 632.634, 'duration': 8.483}, {'end': 644.357, 'text': 'And when they go out, they cost a lot of money to replace.', 'start': 641.617, 'duration': 2.74}, {'end': 649.399, 'text': 'And so we were trying to come up with a code that would look at the different wobblings so they could replace the pieces.', 'start': 644.558, 'duration': 4.841}, {'end': 651.621, 'text': 'instead of having to replace a whole aerator.', 'start': 649.839, 'duration': 1.782}, {'end': 656.107, 'text': 'So they could replace the bushing instead of having to go in there and replace the whole fan unit.', 'start': 651.882, 'duration': 4.225}], 'summary': 'Utilized inline editing to predict maintenance for sewage plant aerators, saving costs by replacing specific parts.', 'duration': 29.036, 'max_score': 627.071, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/3C9E2yPBw7s/pics/3C9E2yPBw7s627071.jpg'}], 'start': 200.459, 'title': 'Jupyter notebook basics and environment management', 'summary': 'Covers creating and managing environments in jupyter notebook using conda and pip, accessing tools like jupyter lab and rstudio, and introduces basics such as setting up the environment, running code cells, managing kernels, and highlighting the limitations of multi-processing and the convenience of inline editing and output.', 'chapters': [{'end': 334.156, 'start': 200.459, 'title': 'Creating and managing environments in jupyter notebook', 'summary': 'Discusses creating and managing environments in jupyter notebook, including using conda and pip for package installation, and accessing tools like jupyter lab and rstudio within the environment.', 'duration': 133.697, 'highlights': ['Jupyter Notebook, conda, and pip usage The chapter explains the usage of Jupyter Notebook, conda, and pip for package installation and environment management, emphasizing the importance of sticking with either conda or pip to avoid problems with imports and reliance.', 'Accessing tools like Jupyter Lab and RStudio The chapter mentions accessing tools like Jupyter Lab and RStudio within the environment and highlights the preference for using Jupyter Notebook and occasionally RStudio for wrapping everything in the environment.', 'File organization and creation history The chapter details the file organization and creation history within the environment, with folders located on the D drive and files dating back to the last couple of months, including tutorials and other materials.']}, {'end': 665.718, 'start': 334.497, 'title': 'Jupyter notebook basics', 'summary': 'Introduces the basics of using jupyter notebook for python programming, covering topics such as setting up the environment, running code cells, and managing kernels, with emphasis on the limitations of multi-processing and the convenience of inline editing and output.', 'duration': 331.221, 'highlights': ['Jupyter Notebook allows for easy setup and running of Python code, with the ability to create, edit, and execute code cells individually or in sequence. The Jupyter Notebook provides a user-friendly interface for creating and running Python code, allowing for easy editing and execution of code cells individually or in sequence.', "The chapter highlights the limitation of Jupyter Notebook in handling multi-processing, as it only opens a single kernel for execution, leading to potential issues with multi-processing functionality. It's important to note the limitation of Jupyter Notebook in handling multi-processing, as it only opens a single kernel for execution, potentially causing issues with multi-processing functionality.", 'The inline editing and output feature in Jupyter Notebook is emphasized, showcasing its usefulness for interactive presentations and data analysis tasks, as demonstrated in a real-world scenario of predicting maintenance needs for industrial equipment. The inline editing and output feature in Jupyter Notebook is highlighted for its usefulness in interactive presentations and data analysis tasks, such as predicting maintenance needs for industrial equipment, providing a real-world example of its practical application.']}], 'duration': 465.259, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/3C9E2yPBw7s/pics/3C9E2yPBw7s200459.jpg', 'highlights': ['The chapter explains the usage of Jupyter Notebook, conda, and pip for package installation and environment management, emphasizing the importance of sticking with either conda or pip to avoid problems with imports and reliance.', 'Accessing tools like Jupyter Lab and RStudio within the environment and highlights the preference for using Jupyter Notebook and occasionally RStudio for wrapping everything in the environment.', 'The chapter details the file organization and creation history within the environment, with folders located on the D drive and files dating back to the last couple of months, including tutorials and other materials.', 'Jupyter Notebook allows for easy setup and running of Python code, with the ability to create, edit, and execute code cells individually or in sequence.', "It's important to note the limitation of Jupyter Notebook in handling multi-processing, as it only opens a single kernel for execution, potentially causing issues with multi-processing functionality.", 'The inline editing and output feature in Jupyter Notebook is highlighted for its usefulness in interactive presentations and data analysis tasks, such as predicting maintenance needs for industrial equipment, providing a real-world example of its practical application.']}, {'end': 1141.685, 'segs': [{'end': 756.385, 'src': 'heatmap', 'start': 701.953, 'weight': 0, 'content': [{'end': 707.757, 'text': "Enter And it won't print, hope to see you in class soon, until I click on this cell and run it.", 'start': 701.953, 'duration': 5.804}, {'end': 710.319, 'text': "And then you'll see, hope to see you in class soon.", 'start': 708.137, 'duration': 2.182}, {'end': 711.72, 'text': 'So you have a lot of control.', 'start': 710.339, 'duration': 1.381}, {'end': 713.382, 'text': 'You can work on one piece of code.', 'start': 711.82, 'duration': 1.562}, {'end': 714.963, 'text': "Maybe you're loading your variables up.", 'start': 713.542, 'duration': 1.421}, {'end': 718.268, 'text': 'and then you can start executing the code based on those variables.', 'start': 715.283, 'duration': 2.985}, {'end': 722.554, 'text': "But you do have to remember if the problem is in the cell above, you've got to fix that.", 'start': 718.508, 'duration': 4.046}, {'end': 726.039, 'text': "You can't just keep working on the cell below and expect it not to change the answer.", 'start': 722.714, 'duration': 3.325}, {'end': 729.805, 'text': 'Another important thing to notice, this is a title.', 'start': 726.44, 'duration': 3.365}, {'end': 732.908, 'text': 'You know, you use your comments to comment something else.', 'start': 730.646, 'duration': 2.262}, {'end': 738.652, 'text': 'But in Jupyter Notebook, I can come in here to the cell, and I can change the cell type to Markdown.', 'start': 733.248, 'duration': 5.404}, {'end': 745.496, 'text': 'And you can see in Markdown, it changes the colors and everything, and when I run it, you know, I end up with this is a title, this is a bigger title.', 'start': 739.012, 'duration': 6.484}, {'end': 750.34, 'text': "So I can create nice titles in here if I'm working with a project and I'm actually doing a demo.", 'start': 745.757, 'duration': 4.583}, {'end': 752.582, 'text': "I'm actually doing some kind of production.", 'start': 750.66, 'duration': 1.922}, {'end': 756.385, 'text': "I'm showing the graphs, and I've generated the graphs already in my Jupyter notebook.", 'start': 752.602, 'duration': 3.783}], 'summary': 'Jupyter notebook offers control over code, variables, and visual presentation, enabling efficient project work and demos.', 'duration': 36.699, 'max_score': 701.953, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/3C9E2yPBw7s/pics/3C9E2yPBw7s701953.jpg'}, {'end': 781.102, 'src': 'embed', 'start': 756.865, 'weight': 1, 'content': [{'end': 764.291, 'text': "Instead of going back out, putting that into a presentation, I can just open up the notebook, scroll down, add my titles in, and I'm ready to go.", 'start': 756.865, 'duration': 7.426}, {'end': 771.157, 'text': "So you can see right here, it's very useful to be able to tag a box as, in this case, Markdown for our cell.", 'start': 764.311, 'duration': 6.846}, {'end': 774.919, 'text': 'And then I mentioned to you that we can also do our plots in here.', 'start': 771.437, 'duration': 3.482}, {'end': 781.102, 'text': "So let's go ahead and import matplotlibrary as plt, very commonly used that way.", 'start': 775.039, 'duration': 6.063}], 'summary': 'Conveniently create presentations from notebooks, tag cells, and import matplotlibrary for plots.', 'duration': 24.237, 'max_score': 756.865, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/3C9E2yPBw7s/pics/3C9E2yPBw7s756865.jpg'}, {'end': 984.563, 'src': 'embed', 'start': 947.721, 'weight': 3, 'content': [{'end': 951.163, 'text': "It's still doing some plotting in here and coming down for whatever reason.", 'start': 947.721, 'duration': 3.442}, {'end': 955.066, 'text': "If you go to the top, you'll see up here in the tab there's an hourglass.", 'start': 951.424, 'duration': 3.642}, {'end': 957.108, 'text': 'That means this kernel is running.', 'start': 955.446, 'duration': 1.662}, {'end': 958.849, 'text': "We'll go ahead and interrupt this kernel.", 'start': 957.188, 'duration': 1.661}, {'end': 961.131, 'text': "And I'll take a moment to interrupt the kernel and stop it.", 'start': 959.029, 'duration': 2.102}, {'end': 962.872, 'text': "You'll see that shut down in just a minute.", 'start': 961.211, 'duration': 1.661}, {'end': 965.739, 'text': "Another, there's so many cool things you can do with Jupyter.", 'start': 963.459, 'duration': 2.28}, {'end': 966.52, 'text': 'I get so excited.', 'start': 965.759, 'duration': 0.761}, {'end': 967.56, 'text': "It's so simple.", 'start': 966.8, 'duration': 0.76}, {'end': 973.581, 'text': "There's not like a huge number of hidden commands on the page, although certainly there's all kinds of back-end stuff you can do.", 'start': 967.58, 'duration': 6.001}, {'end': 981.322, 'text': "One of the things you can do in here is I can go up to File and if you go under File, you'll see down here Download As,", 'start': 973.841, 'duration': 7.481}, {'end': 984.563, 'text': 'and I can download it as a notebook, which it automatically saves as.', 'start': 981.322, 'duration': 3.241}], 'summary': 'Introduction to interrupting kernels and downloading files in jupyter.', 'duration': 36.842, 'max_score': 947.721, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/3C9E2yPBw7s/pics/3C9E2yPBw7s947721.jpg'}, {'end': 1083.173, 'src': 'embed', 'start': 1043.027, 'weight': 5, 'content': [{'end': 1050.092, 'text': "We clicked up here to rename, but if you're under view, let's say I don't want the header on, I can still just go under file and rename.", 'start': 1043.027, 'duration': 7.065}, {'end': 1054.996, 'text': "So if I don't want to see the header and I want that extra screen space, which I like, I can toggle that on and off.", 'start': 1050.312, 'duration': 4.684}, {'end': 1058.719, 'text': 'I can toggle the toolbar off, put that back on with all those shortcuts.', 'start': 1055.076, 'duration': 3.643}, {'end': 1061.12, 'text': 'And to wrap it up, one more reference.', 'start': 1059.139, 'duration': 1.981}, {'end': 1062.701, 'text': 'Let me just close these out.', 'start': 1061.381, 'duration': 1.32}, {'end': 1069.546, 'text': 'If you do Jupyter Notebook repositories on Git and I just go to trending notebook repositories on the GitHub.', 'start': 1063.142, 'duration': 6.404}, {'end': 1072.227, 'text': "you'll see all kinds of stuff on here that you can go practice with.", 'start': 1069.546, 'duration': 2.681}, {'end': 1073.989, 'text': 'You can pull what somebody else is working on.', 'start': 1072.468, 'duration': 1.521}, {'end': 1077.431, 'text': 'They have Practical AI, MIT Deep Learning, TF2 course.', 'start': 1074.009, 'duration': 3.422}, {'end': 1079.432, 'text': 'TensorFlow examples.', 'start': 1077.951, 'duration': 1.481}, {'end': 1083.173, 'text': "That's the Google TensorFlow I mentioned earlier, which is a neural network.", 'start': 1079.472, 'duration': 3.701}], 'summary': 'Demonstrates toggling off header and toolbar for extra screen space. mentions trending jupyter notebook repositories on github like practical ai and tensorflow examples.', 'duration': 40.146, 'max_score': 1043.027, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/3C9E2yPBw7s/pics/3C9E2yPBw7s1043027.jpg'}], 'start': 668.821, 'title': 'Using jupyter notebooks for data visualization and anaconda functionalities', 'summary': 'Discusses using jupyter notebook for data visualization, covering running cells, changing cell types, creating titles, and generating plots inline. it also explores jupyter notebooks and anaconda functionalities such as interrupting and restarting the kernel, downloading files, toggling display options, and accessing resources on github.', 'chapters': [{'end': 909.242, 'start': 668.821, 'title': 'Jupyter notebook for data visualization', 'summary': 'Discusses the use of jupyter notebook for data visualization, demonstrating how to run cells, change cell types to markdown, create titles, and generate plots inline, making it a convenient tool for creating presentations and sharing project information with stakeholders.', 'duration': 240.421, 'highlights': ['Jupyter Notebook allows running cells top to bottom, one at a time, and provides control over the execution of code based on variables. Demonstrates the ability to run cells top to bottom and control the execution of code based on variables.', 'It is possible to change cell types to Markdown in Jupyter Notebook, enabling the creation of titles and structured content within the notebook itself. Shows how to change cell types to Markdown, allowing the creation of structured content and titles within the notebook.', 'The use of Jupyter Notebook for data visualization is convenient as it allows generating and displaying plots inline without the need to switch to a separate environment. Illustrates the convenience of generating and displaying plots inline within the Jupyter Notebook environment, eliminating the need to switch to a separate environment.']}, {'end': 1141.685, 'start': 909.402, 'title': 'Jupyter notebooks and anaconda', 'summary': 'Covers various functionalities of jupyter notebooks and anaconda, including interrupting and restarting the kernel, downloading files in different formats, toggling display options, and accessing resources on github for hands-on practice.', 'duration': 232.283, 'highlights': ['The chapter covers various functionalities of Jupyter Notebooks and Anaconda, including interrupting and restarting the kernel. None', 'The speaker demonstrates how to download files in different formats such as notebook, Python.py file, and HTML from Jupyter Notebooks. None', 'The chapter explains how to toggle display options, such as hiding the header and toolbar for extra screen space. None', 'Accessing resources on GitHub is mentioned as a way to find Jupyter Notebooks for hands-on practice and learning. None']}], 'duration': 472.864, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/3C9E2yPBw7s/pics/3C9E2yPBw7s668821.jpg', 'highlights': ['Jupyter Notebook allows running cells top to bottom, one at a time, and provides control over the execution of code based on variables.', 'The use of Jupyter Notebook for data visualization is convenient as it allows generating and displaying plots inline without the need to switch to a separate environment.', 'It is possible to change cell types to Markdown in Jupyter Notebook, enabling the creation of titles and structured content within the notebook itself.', 'The chapter covers various functionalities of Jupyter Notebooks and Anaconda, including interrupting and restarting the kernel.', 'The speaker demonstrates how to download files in different formats such as notebook, Python.py file, and HTML from Jupyter Notebooks.', 'The chapter explains how to toggle display options, such as hiding the header and toolbar for extra screen space.', 'Accessing resources on GitHub is mentioned as a way to find Jupyter Notebooks for hands-on practice and learning.']}], 'highlights': ['The chapter explains the process of installing Jupyter Notebook using Anaconda, including the recommendation to use Anaconda for installation.', 'The chapter demonstrates multiple ways to access Jupyter Notebook after installation, including using Anaconda Navigator and Anaconda Prompt, as well as directly accessing it through the Anaconda installation.', "It discusses the version options for Anaconda, specifically version 3.7 and 2.7, and the flexibility to work with different Python versions, such as 3.6 for Google's TensorFlow.", 'The chapter details the file organization and creation history within the environment, with folders located on the D drive and files dating back to the last couple of months, including tutorials and other materials.', 'The chapter explains the usage of Jupyter Notebook, conda, and pip for package installation and environment management, emphasizing the importance of sticking with either conda or pip to avoid problems with imports and reliance.', 'The chapter covers various functionalities of Jupyter Notebooks and Anaconda, including interrupting and restarting the kernel.', 'The use of Jupyter Notebook for data visualization is convenient as it allows generating and displaying plots inline without the need to switch to a separate environment.', "It's important to note the limitation of Jupyter Notebook in handling multi-processing, as it only opens a single kernel for execution, potentially causing issues with multi-processing functionality.", 'The inline editing and output feature in Jupyter Notebook is highlighted for its usefulness in interactive presentations and data analysis tasks, such as predicting maintenance needs for industrial equipment, providing a real-world example of its practical application.']}