Scientific Python Tutorial Workshop | Part 3 | Scikit-Learn & a bit of TensorFlow

Learning Scientific Computing and Machine Learning in Python in a top-down approach by simple coding examples. Today we will cover essential libraries for plotting, data handling and numerical algorithms. Find the repo here: https://github.com/Ceyron/scientific-python-course

Here is Part 1: https://www.youtube.com/watch?v=CIRGYcCasyI
Here is Part 2: https://www.youtube.com/watch?v=csEIJvP4z2s
Here is Part 4 (equivalent to the workshop recording): https://www.youtube.com/watch?v=z_xSsl8iC4g

Link to the Playlist: https://www.youtube.com/watch?v=fJtErsjgk2w&list=PLISXH-iEM4JlMBu-spRORmhmk9mWKxJeG

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📝 : Check out the GitHub Repository of the channel, where I upload all the handwritten notes and source-code files (contributions are very welcome): https://github.com/Ceyron/machine-learning-and-simulation

📢 : Follow me on LinkedIn or Twitter for updates on the channel and other cool Machine Learning & Simulation stuff: https://www.linkedin.com/in/felix-koehler and https://twitter.com/felix_m_koehler

💸 : If you want to support my work on the channel, you can become a Patreon here: https://www.patreon.com/MLsim

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⚙️ My Gear:

(Below are affiliate links to Amazon. If you decide to purchase the product or something else on Amazon through this link, I earn a small commission.)

- 🎙️ Microphone: Blue Yeti: https://amzn.to/3NU7OAs
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- 🎨 Gaomon Drawing Tablet (similar to a WACOM Tablet, but cheaper, works flawlessly under Linux): https://amzn.to/37katmf
- 🔌 Laptop Charger: https://amzn.to/3ja0imP
- 💻 My Laptop (generally I like the Dell XPS series): https://amzn.to/38xrABL
- 📱 My Phone: Fairphone 4 (I love the sustainability and repairability aspect of it): https://amzn.to/3Jr4ZmV

If I had to purchase these items again, I would probably change the following:

- 🎙️ Rode NT: https://amzn.to/3NUIGtw
- 💻 Framework Laptop (I do not get a commission here, but I love the vision of Framework. It will definitely be my next Ultrabook): https://frame.work

As an Amazon Associate I earn from qualifying purchases.

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Timestamps:
00:00:00 Intro & Overview
00:11:15 Sk-Learn: Ordinary Linear Regression (cont.)
00:34:51 Sk-Learn: Linear Regression with Feature Engineering
01:08:03 Sk-Learn: Regularization
01:58:01 Sk-Learn: Linear Regression in High Dimensions
02:22:21 Sk-Learn: Logistic Regression
02:48:50 More on Classification
02:56:51 Sk-Learn: K-Means Clustering
03:32:47 Sk-Learn: PCA Dimensionality Reduction
03:54:21 Sk-Learn: Wrap-Up
04:08:01 Deep Learning Intro
04:23:20 Automatic Differentiation in TensorFlow
04:59:38 Summary & Outlook & Outro

Видео Scientific Python Tutorial Workshop | Part 3 | Scikit-Learn & a bit of TensorFlow канала Machine Learning & Simulation