DS Projects

• Python basic scripts in "01 General"
• Feature Engineering steps in "02 Feature Engineering"
• All different ML Algorithms with Examples"
• Different Boosting Tech with Examples"
  • 01 General
  • 02 Feature Engineering
  • 03 Linear Regression
  • 04 Logistic Regression
  • 05 Polynomial Regression
  • 06 DecisionTree RandomForest
  • 07 Naive Bayes
  • 08 SVM
  • 09 KNN
  • 10 Ridge Lasso Regression
  • 11 KMean Cluster Unsupervised
  • 12 Agglomerative Hierarchy Cluster Unsupervised
  • 13 Apriori Algorithm Association Rule
  • 14 UB CB Recommendation
  • 15 Reinforcement Learning
  • 16 Time Series
  • 17 Boosting_and_CV
  • 18 Projects
  • 19 Libraries

• Basic NLP Code
• Advanced NLP Project
  • 01_DSH_NLP_Basic_Text_Mining
  • 02_DSH_NLP_Advanced_Text_Processing
  • 03_DSH_NLP_ML_(SGDClassifier, LogisticRegression, LogisticRegressionCV, LinearSVC,RandomForestClassifier)
  • 04_DSH_NLP_SpamEmailClassifierUseCase (MultinomialNB)
  • 05_DSH_NLP_Stock Sentiment Analysis UseCase (RandomForestClassifier)
  • 06_DSH_NLP_FakeNewsClassifier_TFIDF
  • 07_DSH_NLP_News_Topics_Clustering (Unsupervised Learning in NLP)
  • 08_DSH_NLP_WordEmbedding Using Keras
  • 09_DSH_NLP_FakeNewsClassifier Using LSTM
  • 10_DSH_NLP_Stock Prediction Using Stacked LSTM
  • 11_DSH_NLP_Encoder_Decoder

• Basic DL Code, Explained Basic Neural Network ANN,CNN,RNN. (CNN with example)
  • Theory on (NN or ANN), CNN Object Detection and Image segmentation(RCNN, FastRCNN, Fater RCNN, YOLO), RNN (LSTM,GRU)
• Advanced DL Concepts, not full project ( -01a_digits_recognition
  • 01b_keras_fashion_mnist_neural_net
  • 02_activation_functions,
  • 03_derivatives
  • 05_loss
  • 06_gradient_descent
  • 07_nn_from_scratch
  • 08_SGD_vs_BGD_vs_miniBGD
  • 09_tensorboard
  • 11_chrun_prediction
  • 12_precision_recall
  • 13_dropout_layer
  • 14_imbalanced
  • 16_cnn_cifar10_small_image_classification
  • 17_data_augmentation
  • 18_transfer_learning
  • 22_word_embedding
  • 23_word2vec_in_gensim
  • 24_tf_data_pipeline_Very_good
  • 25_prefatch_cache_tf_datapipeline_optimization
  • 26_BERT_intro
  • 27_BERT_text_classification
  • 28_tf_serving
  • 29_quantization

• WebScrapping Basic