/MLWithPytorch

Objective of the repository is to learn and build machine learning models using Pytorch. 30DaysofML Using Pytorch

Primary LanguagePython

MLWithPyTorch

30 Days Of Machine Learning Using Pytorch

Objective of the repository is to learn and build machine learning models using Pytorch.

List of Algorithms Covered

📌 Day 1 - Linear Regression
📌 Day 2 - Logistic Regression
📌 Day 3 - Decision Tree
📌 Day 4 - KMeans Clustering
📌 Day 5 - Naive Bayes
📌 Day 6 - K Nearest Neighbour (KNN)
📌 Day 7 - Support Vector Machine
📌 Day 8 - Tf-Idf Model
📌 Day 9 - Principal Components Analysis
📌 Day 10 - Lasso and Ridge Regression
📌 Day 11 - Gaussian Mixture Model
📌 Day 12 - Linear Discriminant Analysis
📌 Day 13 - Adaboost Algorithm
📌 Day 14 - DBScan Clustering
📌 Day 15 - Multi-Class LDA
📌 Day 16 - Bayesian Regression

Let me know if there is any correction. Feedback is welcomed.

References

  • Sklearn Library
  • ML-Glossary