GitHub - SudhanshuBlaze/Machine-Learning: Machine Learning repo, contains implementation of most popularly used ML and DL algorithms. Build basic projects with all those ML algorithms like Naive Bayes, SVM, Random Forest Classifier etc.

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Name		Name	Last commit message	Last commit date
Latest commit History 26 Commits
.ipynb_checkpoints		.ipynb_checkpoints
0 Assignment		0 Assignment
0 resources		0 resources
InternAssignment		InternAssignment
Model		Model
.gitignore		.gitignore
01. Linear Regression .ipynb		01. Linear Regression .ipynb
02. LR-Multiple Variable.ipynb		02. LR-Multiple Variable.ipynb
03. One Hot Encoding.ipynb		03. One Hot Encoding.ipynb
04. train_test_split_demo.ipynb		04. train_test_split_demo.ipynb
05. Logistic regression.ipynb		05. Logistic regression.ipynb
06. Logistic Regression MultiClass.ipynb		06. Logistic Regression MultiClass.ipynb
07. Pandas - Data Analysis.ipynb		07. Pandas - Data Analysis.ipynb
07. Pandas-Merging, Joining, and Concatenating.ipynb		07. Pandas-Merging, Joining, and Concatenating.ipynb
09. Support Vector Machine (Iris ,diabetes).ipynb		09. Support Vector Machine (Iris ,diabetes).ipynb
10. Decision Tree and Random Forest Regressor.ipynb		10. Decision Tree and Random Forest Regressor.ipynb
11. K- Fold Cross Validation.ipynb		11. K- Fold Cross Validation.ipynb
12. KMeans .ipynb		12. KMeans .ipynb
13. Naive Bayes (import model).ipynb		13. Naive Bayes (import model).ipynb
14. Hyper Parameter Tunning.ipynb		14. Hyper Parameter Tunning.ipynb
15. K Nearest Neighbours.ipynb		15. K Nearest Neighbours.ipynb
16. Principal Component Analysis.ipynb		16. Principal Component Analysis.ipynb
17. Recommender Systems.ipynb		17. Recommender Systems.ipynb
18. NLP(spam detection) -NLTK.ipynb		18. NLP(spam detection) -NLTK.ipynb
19. Email spam -spaCy.ipynb		19. Email spam -spaCy.ipynb
19. Text Pre-processing spaCy.ipynb		19. Text Pre-processing spaCy.ipynb
20. Vader Sentiment-Analysis-Project.ipynb		20. Vader Sentiment-Analysis-Project.ipynb
21. Text-Summarizer NLTK.ipynb		21. Text-Summarizer NLTK.ipynb
22. Gradient Descent.ipynb		22. Gradient Descent.ipynb
23. TensorBoard with MNIST.ipynb		23. TensorBoard with MNIST.ipynb
24. Dropout Regularization (exporting the model).ipynb		24. Dropout Regularization (exporting the model).ipynb
25. CNN- Cifar Dataset.ipynb		25. CNN- Cifar Dataset.ipynb
26. Data Augmentation -Flower Dataset.ipynb		26. Data Augmentation -Flower Dataset.ipynb
27. Transfer Learning.ipynb		27. Transfer Learning.ipynb
28. RNN- Text Generation(Other Resources).ipynb		28. RNN- Text Generation(Other Resources).ipynb
29. Word embedding using keras embedding layer.ipynb		29. Word embedding using keras embedding layer.ipynb
Word Embeddings.png		Word Embeddings.png
epochBIG.h5		epochBIG.h5

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Machine Learning repo, contains implementation of most popularly used ML and DL algorithms. Build basic projects with all those ML algorithms like Naive Bayes, SVM, Random Forest Classifier etc.