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Tuesday Tip #45: How to read the scikit-learn documentation 📚
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Hi Reader, Last week, I recorded the FINAL 28 LESSONS 🎉 for my upcoming course, Master Machine Learning with scikit-learn. That's why you didn't hear from me last week! 😅 I edited one of those 28 videos and posted it on YouTube. That video is today's tip, which I'll tell you about below! 👉 Tip #45: How to read the scikit-learn documentationIn order to become truly proficient with scikit-learn, you need to be able to read the documentation. In this video lesson, I’ll walk you through the five main pages and page types that you need to be familiar with:
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👋 See you next Tuesday!Did you like this week’s tip? Please forward it to a friend or share the video with your favorite online community. It really helps me out! - Kevin P.S. What's your LinkedIn productivity score?​ Did someone AWESOME forward you this email? Sign up here to receive Data Science tips every week! |
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Kevin Markham
Join 25,000+ aspiring Data Scientists and receive Python & Data Science tips every Tuesday!
Hi Reader, I'm really proud of this week's tip because it covers a topic (data leakage) that took me years to fully understand. 🧠It's one of those times when I feel like I'm truly contributing to the collective wisdom by distilling complex ideas into an approachable format. 💡 You can read the tip below 👇 or on my blog. 🔗 Link of the week Building an AI Coach to Help Tame My Monkey Mind (Eugene Yan) In this short post, Eugene describes his experiences calling an LLM on the phone for coaching:...
Hi Reader, happy Tuesday! My recent tips have been rather lengthy, so I'm going to mix it up with some shorter tips (like today's). Let me know what you think! 💬 🔗 Link of the week A stealth attack came close to compromising the world's computers (The Economist) If you haven't heard about the recent "xz Utils backdoor", it's an absolutely fascinating/terrifying story! In short, a hacker (or team of hackers) spent years gaining the trust of an open-source project by making helpful...
Hi Reader, Today's tip is drawn directly from my upcoming course, Master Machine Learning with scikit-learn. You can read the tip below or watch it as a video! If you're interested in receiving more free lessons from the course (which won't be included in Tuesday Tips), you can join the waitlist by clicking here: Yes, I want more free lessons! 👉 Tip #43: Should you discretize continuous features for Machine Learning? Let's say that you're working on a supervised Machine Learning problem, and...