In this repo, all about Machine Learning and I covered both Supervised and Unsupervised Learning Techniques with Practical Implementation. Everything from scratch and I solved a lot of different problems with different Machine Learning techniques either related to Healthcare, E-commerce, Sports, or Daily Business Issues.

Click to see the complete documentation of this repository:
https://drive.google.com/file/d/1deQBEKKWY__nUC1uI--UlsC-BRU7oS9B/view

Click to see my book on Machine Learning:
https://www.amazon.com/gp/product/B07Q5MK6DS/

The Topic that are covered in this repository are:

1. Supervised Machine Learning
   1. Classfication
      1. Naive Bayes Classifier(NB)
      2. Logisttic Regression
      3. k-Nearest Neighbors(kNN)
      4. Decision Tree Classifier
      5. Random Forrest Classifier
      6. Support Vector Machine(SVC)
   2. Regression
      
      1. Liner regression
      2. Decision Tree Regression
      3. Random Forrest Regression
      4. Support Vector Regression(SVR)
2. Unsupervised Machine Learning
   1. Association Rule
      1. Apriori Algorithm
      2. FP Growth Algorithm
   2. Clustering
      1. k-Mean Clustering
      2. Hierarchical Clustering
   3. Dimensionality Reduction
      1. Principal Component Analysis(PCA)
      2. Linear Discriminant Analysis (LDA)