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ML for Beginners – Introduction to Linear Regression – Q&A

Microsoft Reactor
114K subscribers
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508 views Streamed 1 year ago #AI #DeepLearning #machine
🤖 Welcome to the fourth of our Machine Learning livestreams! In this episode, @jimbobbennett and Bea Stollnitz from Microsoft chat about linear regression, run some real world examples using Jupyter notebooks, and answer real-world questions ML from our live audience. This is part 4 of a number of live streams. This video is a live walkthrough of the ML for Beginners video series from Microsoft, available at    • Machine Learning for Beginners  . 00:00 - Intro 00:56 - Introducing Bea Stollnitz 02:55 - Introducing ML for beginners - https://aka.ms/ml-beginners 04:00 - The ML for beginners video series - https://aka.ms/ml-beginners-videos 06:50 - What is linear regression? 14:40 - How to handle outliers in your data 17:31 - Unbalanced data sets 19:50 - SMOTE for handling unbalanced data - https://towardsdatascience.com/smote-... 21:50 - Is it useful to learn machine learning? 25:14 - Python libraries for SMOTE - https://imbalanced-learn.org/dev …...more
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Intro

0:00

Introducing Bea Stollnitz

0:56

Introducing ML for beginners

2:55

The ML for beginners video series

4:00

What is linear regression?

6:50

How to handle outliers in your data

14:40

Unbalanced data sets

17:31

SMOTE for handling unbalanced data

19:50

Is it useful to learn machine learning?

21:50

Python libraries for SMOTE

25:14

Will a PhD help with a career in ML?

27:50

Get the values of m and b in y= b + mx

34:05

Let's work through code to clean pumpkin data

35:05

How to handle missing data in linear regression

38:35

Let's work through code to clean pumpkin data

39:25

Identifying duplicates in data when you have multiple representations of the same thing. Maybe GPT4 can help?

45:23

RLHF - reinforcement learning from human feedback

49:30

Data drift

53:40

Filling missing values with forward and back Filling

56:25
ML for Beginners – Introduction to Linear Regression – Q&A
🤖 Welcome to the fourth of our Machine Learning livestreams! In this episode, @jimbobbennett and Bea Stollnitz from Microsoft chat about linear regression, run some real world examples using Jupyter notebooks, and answer real-world questions ML from our live audience. This is part 4 of a number of live streams. This video is a live walkthrough of the ML for Beginners video series from Microsoft, available at    • Machine Learning for Beginners  . 00:00 - Intro 00:56 - Introducing Bea Stollnitz 02:55 - Introducing ML for beginners - https://aka.ms/ml-beginners 04:00 - The ML for beginners video series - https://aka.ms/ml-beginners-videos 06:50 - What is linear regression? 14:40 - How to handle outliers in your data 17:31 - Unbalanced data sets 19:50 - SMOTE for handling unbalanced data - https://towardsdatascience.com/smote-... 21:50 - Is it useful to learn machine learning? 25:14 - Python libraries for SMOTE - https://imbalanced-learn.org/dev/refe... 27:50 - Will a PhD help with a career in ML? 34:05 - Get the values of m and b in y= b + mx 35:05 - Let's work through code to clean pumpkin data 38:35 - How to handle missing data in linear regression 39:25 - Let's work through code to clean pumpkin data 45:23 - Identifying duplicates in data when you have multiple representations of the same thing. Maybe GPT4 can help? 49:30 - RLHF - reinforcement learning from human feedback 53:40 - Data drift 56:25 - Filling missing values with forward and back Filling #MachineLearning #AI #MLforBeginners #ML #AI #DeepLearning #DataScience #jupyternotebooks #scikitlearn 📚 Learn more: This course is based on the free, open source, 26 lesson ML For Beginners curriculum from Microsoft, which can be found at https://aka.ms/ml-beginners. You can chat with us on the Microsoft Python Discord server. Join at http://aka.ms/python-discord-invite if you haven’t joined already and ask your questions on the #machine-learning channel. This course does not cover AI or Data Science. 🎓 To learn more about these topics, check out our beginner's curriculum: AI for Beginners - https://aka.ms/ai-beginners Data Science for Beginners - https://aka.ms/datascience-beginners Python for Beginners -    • Python for Beginners   📣 Feel free to leave us a comment below, and don't forget to like 👍, subscribe, and ring that bell 🔔 so you don't miss our upcoming episodes: https://aka.ms/Reactor/Subscribe-YouTube 🤝 Connect with us: Homepage: https://aka.ms/Reactor Facebook: https://fb.com/MicrosoftReactor Twitter:   / msftreactor   Meetup: http://meetup.com/pro/microsoft-reactor/ About Microsoft Reactor: Reactors are community spaces where technology professionals meet, learn, and connect - to both their local peers as well as industry-leading ideas and technology from Microsoft, partners, and the open source community. With a diverse mix of workshops, presentations, and networking events customized for each city, there’s something for everyone – whether you’re just getting started or working on complex projects. Our programming is always free and inclusive of a broad set of products, tools, and technologies. [eventID:18908]

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Microsoft Reactor

114K subscribers
ML for beginners: classic Machine Learning for all
Learn classical ML
Machine Learning for Beginners
by Microsoft Developer
Live chat replay is not available for this video.