Project 1:
Pandas (for basic understanding)
Project 2:
Exploratory Data Analysis on Haberman Dataset
Project 3:
Implementing TFIDF vectorizer
Project 4:
Implement RandomSearchCV with k fold cross-validation on KNN
Project 5:
Compute Performance metrics without Sklearn
Project 6:
Apply Naive Bayes on Donors Choose dataset
Project 7:
Implement SGD Classifier with Logloss and L2 regularization Using SGD without using sklearn
Project 8:
Behavior of Linear Mode+ls
Project 9:
Apply Decision Trees on Donors Choose the dataset
Project 10:
Application of Bootstrap samples in Random Forest
Project 11:
Apply GBDT on Donors Choose dataset
Project 12:
Clustering on Graph Dataset
Project 13:
Recommendation Systems and Truncated SVD SGD algorithm to predict ratings
Project 14:
Microsoft Malware Detection
Project 15:
Facebook Friend Recommendation
Project 16:
SQL Assignment on IMDB data
Project 17:
Working with Callbacks
Project 18:
Transfer Learning
Project 19:
Document Classification with CNN
Project 20:
LSTM on Donors Choose
Project 21:
CNN on CIFR
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