- Steps of machine learning procedure.
- tools to help you work better and faster.
- algorithms from scratch to gain the deep understanding of how Machine learning works and how it affects on data.
We all know getting into Machine Learning it is all about the mathematics , statistics and probabilities behind every model and visualizing the important insights. In this file you will know :
- How to implement (Linear Regression , Normal equation , Logistic Regression , K-Means clustering , Associaton rule - Apriori , simple reinforcement learning techniques ) from scratch using only numpy and pandas.
- Important visualizations to gain better understanding about how Machine Learning works in depth.
- algorithms from scratch to gain the deep understanding of how Machine learning works and how it affects the data.
after knowing the basics and methods to deal with machine learning problems , tools and frameworks will make things easier with sklearn. In this file you will know :
- tools to help you work better and faster.
- more advanced visualizations.
- advanced tools that takes you the extra mile.
What Tools you will need:
pandas , numpy , sklearn , matplotlib , seaborn , apyori