/machine_learning_practice

Learning ML using Octave, Scikit-learn and Tensorflow

Primary LanguageJupyter Notebook

Math

  1. Linear Algebra - https://ocw.mit.edu/courses/mathematics/18-06-linear-algebra-spring-2010/
  2. Calculus - https://www.youtube.com/playlist?list=PLZHQObOWTQDMsr9K-rj53DwVRMYO3t5Yr
  3. Probability - https://www.edx.org/course/introduction-probability-science-mitx-6-041x-2

Data Science

  1. Python - https://www.kaggle.com/learn/python
  2. Pandas (data manipulation) - https://www.kaggle.com/learn/pandas
  3. Matplotlib (data visualisation) - https://www.youtube.com/watch?v=qErBw-R2Ybk
  4. Seaborn (data visualisation) - https://www.kaggle.com/learn/data-visualisation

Machine Learning

  1. Machine Learning by Andrew Ng - https://www.coursera.org/learn/machine-learning
  2. Scikit-learn (off-the-shelf machine learning algorithms) - https://www.youtube.com/watch?v=HC0J_SPm9co
  3. Tensorflow (Google's machine learning library) - https://developers.google.com/machine-learning/crash-course/ml-intro

Book

http://index-of.es/Varios-2/Hands%20on%20Machine%20Learning%20with%20Scikit%20Learn%20and%20Tensorflow.pdf

Projects

Titanic Kaggle Competition- https://www.kaggle.com/c/titanic