ML-DL-NLP-resource-notebooks

This repository contains all resources and notebook implementations of Machine Learning, Deep Learning and Natural Language Processing concepts.

Name		Name	Last commit message	Last commit date
Latest commit History 10 Commits
All Important Cheat Sheets by MIT & Stanford University AI.pdf		All Important Cheat Sheets by MIT & Stanford University AI.pdf
Case_Study_Debugging_in_Classification.ipynb		Case_Study_Debugging_in_Classification.ipynb
Case_Study_Debugging_in_Regression.ipynb		Case_Study_Debugging_in_Regression.ipynb
Churn_Modelling.csv		Churn_Modelling.csv
Data Augmentation--Keras-checkpoint.ipynb		Data Augmentation--Keras-checkpoint.ipynb
Data Augmentation--Keras.ipynb		Data Augmentation--Keras.ipynb
Hands On Alexnet.ipynb		Hands On Alexnet.ipynb
HypParamSelection.ipynb		HypParamSelection.ipynb
OptimizeCNNwithKerasTuner.ipynb		OptimizeCNNwithKerasTuner.ipynb
PCA_tSNE_code.ipynb		PCA_tSNE_code.ipynb
README.md		README.md
classification algo in various scenarios.pdf		classification algo in various scenarios.pdf
cnn.pdf		cnn.pdf
decision trees.pdf		decision trees.pdf
deep learning intro.pdf		deep learning intro.pdf
dimensionality reduction.pdf		dimensionality reduction.pdf
dog.jpg		dog.jpg
eda.pdf		eda.pdf
ensemble models.pdf		ensemble models.pdf
feature engineering.pdf		feature engineering.pdf
knn.pdf		knn.pdf
linear regression.pdf		linear regression.pdf
locality-sensitive-hashing-for-cosine-similarity.ipynb		locality-sensitive-hashing-for-cosine-similarity.ipynb
logistic regression.pdf		logistic regression.pdf
naive bayes.pdf		naive bayes.pdf
out.pdf		out.pdf
performance measurement of models.pdf		performance measurement of models.pdf
probability and statistics.pdf		probability and statistics.pdf
pseudo residual revisited.pdf		pseudo residual revisited.pdf
recommendation systems.pdf		recommendation systems.pdf
rnn.pdf		rnn.pdf
solving optimisation problems.pdf		solving optimisation problems.pdf
svm.pdf		svm.pdf

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