Machine Learning

A series of articles dedicated to machine learning and statistics. All codes and exercises of this section are hosted on GitHub in a dedicated repository :

Gentle Introduction to Linear Regression in Pytorch : Linear Regression with PyTorch explained clearly with code example.

Awesome Introduction to Logistic Regression in PyTorch- : We’ll explore Logits Algorithm with Hello World Datset ML i.e. MNIST.

Innovative Explanation to ML Model’s Interpretability : Demystifying Black Box ML Models.

Machine Learning in a NutShell : Beginner’s Guide to Machine Learning Algorithms.

Complete Guide to Machine Learning Evaluation Metrics :Machine Learning Performance Metrics core concepts discussion in simple way!

Data Shapely: Data valuation for Machine Learning : A first approach to exploring Data Shapley Algorithm for Machine Learning.

Building Flask REST App with Flask-Restful : Detailed Approach to Productionize ML Models with Flask REST APIS.

ML Android App Development with Retrofit & Flask REST API. : One of first kind of Android App Developed with Retrofit (JAVA API) and Flask Rest-Plus (Python API).

Machine learning Cheat Sheat Naive Bayes :A Quick pointers for Machine Learning Algorithms core concepts.

Machine learning Cheat Sheat KNN Algorithm :A Quick pointers for Machine Learning Algorithms core concepts.