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