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Project based Learning

Written by: Mansi

As Machine Learning (ML) and Artificial Intelligence (AI) has widespread applications rangining in almost entire sphere of our lives, AI and ML are becoming increasingly important for all players in the field of Computer Science.

 

While text books and online couses are non negotiable, projects have proved to be gem for every Machine Learning enthusiast . One can never really master ML without investing his/her time in real-life practical experiments – Machine Learning projects. Here is a list of programming tutorials in which learners can build Machine Learning application from scratch. However, these projects will be beneficial only when one is having crystal clear concepts.

 

 

A previous blog of mine Machine Learning for Beginners contains resources/ online free courses for Machine Learning.

 

 

Prerequisites:

 

  1. Machine Learning by Andrew NG

  2. Basic knowledge of Python is required.

 

Projects:

 

Here is a list of standard Machine Learning projects ranging from beginners to advanced.

 

 

  1. Write Simple Linear Regression from Scratch in Python

  2. Stock Price Predictor :

    Algorithm used : Linear Regression

    Refer Kaggle for awesome dataset. Also, refer other kaggle kernels for Stock Price Prediction.

  3. Music Genre Classification:

    Algorithm used: Logistic Regression

  4. Build your own Neural Network from Scratch

  5. Using Neural Networks to recognize handwritten digits

  6. YOLO Object Detection with OpenCV and Python

  7. Twitter Sentiment Analysis

  8. Sentiment Analysis using Neural Networks

  9. Face Recognition with OpenCV Python and Machine Learning

  10. Image Stitching with OpenCV and Python

  11. Object Detection with Mask-R-CNN

 

Some of these tutorials may have direct codes. Try coding yourself referring the documentation or idea shared from scratch (without using built in functions).

Happy Coding!

 

 

 

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