LDA (Linear Discriminant Analysis) In Python – ML From Scratch 14 – Python Tutorial

///LDA (Linear Discriminant Analysis) In Python – ML From Scratch 14 – Python Tutorial

LDA (Linear Discriminant Analysis) In Python – ML From Scratch 14 – Python Tutorial

FavoriteLoadingAdd to favorites

Get my Free NumPy Handbook:

In this Machine Learning from Scratch Tutorial, we are going to implement the LDA algorithm using only built-in Python modules and numpy. LDA (Linear Discriminant Analysis) is a feature reduction technique and a common preprocessing step in machine learning pipelines. We will learn about the concept and the math behind this popular ML algorithm, and how to implement it in Python.

⭐ Kite is a free AI-powered coding assistant that will help you code faster and smarter. The Kite plugin integrates with all the top editors and IDEs to give you smart completions and documentation while you’re typing. I’ve been using Kite for 6 months and I love it!

🚀🚀 Get access to the ML notebooks on Patreon: 🚀🚀

If you enjoyed this video, please subscribe to the channel!

The code can be found here:

Further readings:

You can find me here:
Website:
Twitter:
GitHub:

#Python #MachineLearning

source

By |2020-12-31T11:35:40+00:00December 31st, 2020|Python Video Tutorials|17 Comments

17 Comments

  1. Houda CHAKIR December 31, 2020 at 11:35 am - Reply

    THANK YOU SO MUCH

  2. shafil hosain December 31, 2020 at 11:35 am - Reply

    excellent explanation, Many thanks

  3. rohan devaki December 31, 2020 at 11:35 am - Reply

    you are nicely reading the ppt, very good, 😒
    try to explain it , dont just read it.

  4. 최진영 December 31, 2020 at 11:35 am - Reply

    When I use this code to sklearn.datasets.load_digits, it occurs singular matrix error when calculate np.linalg.inv(SW).
    Why this occurs?

  5. Sujal Bhagat December 31, 2020 at 11:35 am - Reply

    It is great video. Can you send me the code into email: sujalbhagat97@gmail.com

  6. Mostafa Shahhosseini December 31, 2020 at 11:35 am - Reply

    I didn't understand what's the mathematical references of your work. Why did you use that transformation? is it the same with SVD? please note the reference or some keywords for me to study more about the mathematical stuff related to the transformation you made use of that. thanks

  7. Kurnia Adi C December 31, 2020 at 11:35 am - Reply

    permission to learn sir

  8. prashant sharma December 31, 2020 at 11:35 am - Reply

    hi getting this error,. still LDA is able to reduce the dimensions to 2
    "Value 'eigenvectors' is unsubscriptable"
    and why cant we sort the idxs with eign vectors argument?

    update: solved that issue by converting the eignvectors to numpy array… thankx to you , my programing skills are getting better.

  9. Ayush Koul December 31, 2020 at 11:35 am - Reply

    Are you gonna do a playlist for NN from scratch?

  10. Chenyong Miao December 31, 2020 at 11:35 am - Reply

    Finally, finished learning your 14 ML videos. Learned a lot about ML algorithms and numpy skills. Thanks a lot !

  11. Anudeep December 31, 2020 at 11:35 am - Reply

    One of the recent interesting works in DL is Batch Normalization.
    I tried a lot, understanding online, how to implement batch Norm from scratch, but couldn't understand.
    My main problem is understanding Backpropagation in Batch Norm. Can you do a video on it, it'll be very helpful or at least share any resources (if you have any) for backpropagation in Batch Norm.

  12. John Parker December 31, 2020 at 11:35 am - Reply

    Great Work!
    PS: Please make video on on implementing CNN algorithm. It will mean a lot of help for academic students

  13. mahta zarean December 31, 2020 at 11:35 am - Reply

    hi great job .can you also make a viedo on EM(expectation maximization)?tnx alot

  14. Rajganesh Pandurangan December 31, 2020 at 11:35 am - Reply

    of topic. what are your thoughts on Andrew-ng DL course? some feedback says it's hard to understand the Math. if you know the high school math basics, is it possible to follow that course?

  15. Daniel Weikert December 31, 2020 at 11:35 am - Reply

    The biggest thing I am struggling with are the shapes for the neural networks, data feeding in the e.g Embedding layer and reshapings. Is this a topic you can recommend a good learning material or even dive into in one of your videos?
    Thanks

  16. Biranchi Narayan Nayak December 31, 2020 at 11:35 am - Reply

    Excellent tutorial on PCA and LDA

  17. Huy Nguyễn December 31, 2020 at 11:35 am - Reply

    first again!

Leave A Comment

*