GitHub - all4one-max/LEARN-DATA-SCIENCE

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Name		Name	Last commit message	Last commit date
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.ipynb_checkpoints		.ipynb_checkpoints
Decision_Tree_NOTES		Decision_Tree_NOTES
FEATURE_SCALING_NOTES		FEATURE_SCALING_NOTES
IMAGE CAPTIONING PROJECT		IMAGE CAPTIONING PROJECT
KERAS NOTES		KERAS NOTES
KNN NOTES		KNN NOTES
LOGISTIC_REGRESSION_NOTES		LOGISTIC_REGRESSION_NOTES
NAIVE_BAYES_NOTES		NAIVE_BAYES_NOTES
NEURAL NETWORKS NOTES		NEURAL NETWORKS NOTES
PCA_Notes		PCA_Notes
SQL		SQL
TENSORFLOW NOTES		TENSORFLOW NOTES
13. MNIST-Tensorflow.ipynb		13. MNIST-Tensorflow.ipynb
5. CNN-MNIST.ipynb		5. CNN-MNIST.ipynb
API ADV.pdf		API ADV.pdf
API ASSIGNMENT.ipynb		API ASSIGNMENT.ipynb
API.pdf		API.pdf
APIs - 1.ipynb		APIs - 1.ipynb
APIs - 2.ipynb		APIs - 2.ipynb
CODE - LOGISTIC REGRESSION.ipynb		CODE - LOGISTIC REGRESSION.ipynb
CODING NINJA DATA SCIENCE AND ML 60% CERTIFICATE.pdf		CODING NINJA DATA SCIENCE AND ML 60% CERTIFICATE.pdf
CODING NINJA DATA SCIENCE AND ML 90% CERTIFICATE.pdf		CODING NINJA DATA SCIENCE AND ML 90% CERTIFICATE.pdf
CODING_NINJA_Classification Measures.ipynb		CODING_NINJA_Classification Measures.ipynb
CONVOLUTIONAL NEURAL NETWORK.ipynb		CONVOLUTIONAL NEURAL NETWORK.ipynb
DECISION TREES.ipynb		DECISION TREES.ipynb
DIABETES DATASET.ipynb		DIABETES DATASET.ipynb
Decision Tree Implementation.ipynb		Decision Tree Implementation.ipynb
GridSearchCV.ipynb		GridSearchCV.ipynb
IMPLEMENTATION OF NAIVE BAYES.ipynb		IMPLEMENTATION OF NAIVE BAYES.ipynb
INTRO TO ML (BOSTON DATASET TRAINING AND PREDICTION USING LINEAR REGRESSION).ipynb		INTRO TO ML (BOSTON DATASET TRAINING AND PREDICTION USING LINEAR REGRESSION).ipynb
K - NEAREST NEIGHBOURS.ipynb		K - NEAREST NEIGHBOURS.ipynb
KERAS.ipynb		KERAS.ipynb
KMeans.ipynb		KMeans.ipynb
KNN Scratch.ipynb		KNN Scratch.ipynb
LINEAR REGRESSION.ipynb		LINEAR REGRESSION.ipynb
LINEAR REGRESSION.pdf		LINEAR REGRESSION.pdf
MULTI-VARIABLE REGRESSION AND GRADIENT DESCENT.ipynb		MULTI-VARIABLE REGRESSION AND GRADIENT DESCENT.ipynb
MULTIVARIABLE REGRESSION AND GRADIENT DESCENT.pdf		MULTIVARIABLE REGRESSION AND GRADIENT DESCENT.pdf
Movie-Reviews-SKLearn-CountVectorizer.ipynb		Movie-Reviews-SKLearn-CountVectorizer.ipynb
NATURAL LANGUAGE PROCESSING.ipynb		NATURAL LANGUAGE PROCESSING.ipynb
NEURAL NETWORK - 1.ipynb		NEURAL NETWORK - 1.ipynb
NEURAL NETWORK - 2.ipynb		NEURAL NETWORK - 2.ipynb
NumPy ASSIGNMENT.ipynb		NumPy ASSIGNMENT.ipynb
NumPy.ipynb		NumPy.ipynb
PANDAS ASSIGNMENT.ipynb		PANDAS ASSIGNMENT.ipynb
PANDAS.ipynb		PANDAS.ipynb
PCA - 2D.ipynb		PCA - 2D.ipynb
PCA - 3D.ipynb		PCA - 3D.ipynb
PCA ON IMAGES.ipynb		PCA ON IMAGES.ipynb
PLOTTING GRAPHS ASSIGNMENT.ipynb		PLOTTING GRAPHS ASSIGNMENT.ipynb
PLOTTING GRAPHS.ipynb		PLOTTING GRAPHS.ipynb
README.md		README.md
RECURRENT NEURAL NETWORK.ipynb		RECURRENT NEURAL NETWORK.ipynb
Random Forest vs Decision Trees.ipynb		Random Forest vs Decision Trees.ipynb
SEABORN.ipynb		SEABORN.ipynb
SEABORN.pdf		SEABORN.pdf
SQL BASIC.pdf		SQL BASIC.pdf
SQL-Cheat-Sheet.pdf		SQL-Cheat-Sheet.pdf
SQLite ASSIGNMENT.ipynb		SQLite ASSIGNMENT.ipynb
SQLite.ipynb		SQLite.ipynb
STATISTICS.ipynb		STATISTICS.ipynb
SVM-Iris.ipynb		SVM-Iris.ipynb
SVM.ipynb		SVM.ipynb
SVRBoston.ipynb		SVRBoston.ipynb
TABLEAU VISUALIZATIONS.pdf		TABLEAU VISUALIZATIONS.pdf
TENSOR FLOW.ipynb		TENSOR FLOW.ipynb
WEB SCRAPPING - BEAUTIFUL SOUP ASSIGNMENT.ipynb		WEB SCRAPPING - BEAUTIFUL SOUP ASSIGNMENT.ipynb
WEB SCRAPPING - BEAUTIFUL SOUP.ipynb		WEB SCRAPPING - BEAUTIFUL SOUP.ipynb
WEB SCRAPPING - SELENIUM.ipynb		WEB SCRAPPING - SELENIUM.ipynb
WEB SCRAPPING ADVANCED SELENIUM.ipynb		WEB SCRAPPING ADVANCED SELENIUM.ipynb
WEB SCRAPPING SELENIUM - ASSIGNMENTS.ipynb		WEB SCRAPPING SELENIUM - ASSIGNMENTS.ipynb
WORKING WITH FILES - 2.ipynb		WORKING WITH FILES - 2.ipynb
WORKING WITH FILES - ASSIGNMENT.ipynb		WORKING WITH FILES - ASSIGNMENT.ipynb
WORKING WITH FILES.ipynb		WORKING WITH FILES.ipynb
advance_sql.pdf		advance_sql.pdf
data science sql.pdf		data science sql.pdf
indexing and sqlite.pdf		indexing and sqlite.pdf

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SO IN THE SUMMER OF 2020 I TOOK A COURSE OF DATA SCIENCE AND ML FROM CODING NINJAS.

AS A PART OF THE COURSE I LEARNT GIT, WHICH USED TO BE QUITE OVERWHELMING EARLIER. BUT NOW IT SEEMS FUN.

SO I DECIDED TO MAKE A REPOSITORY OF ALL THE THINGS I LEARNT (BASICALLY ALL THE CODES I WROTE AND SOME NOTES I GOT).

NOW, AS A PART OFTHE COURSE I DID LIKE 10-15 PROJECTS WHICH TOOK A HELL LOT OF A TIME. I COULD HAVE COMMITED THOSE PROJECTS IN THIS REPO, BUT THEN IT WOULD BE UNETHICAL SINCE I SCORED 100% IN ALL OF THEM AND SOMEBODY COULD HAVE SIMPLY SUBMIT MY PROJECT. THEREFORE, I MADE SURE TO REMOVE ALL THE PROJECT FILES. ALTHOUGH IF YOU WANT TO KNOW THE PROBLEMS I SOLVED, FEEL FREE TO MAIL ME, I WILL GIVE SOME CHALLENGING TASK TO YOU AND EVEN BETTER IF YOU ARE ABLE TO SOLVE THE TASK I WILL MERGE YOUR BRANCH AND IN DOING SO I WILL LEARN HOW TO USE GIT PULL REQUEST. WIN WIN HUH:)

HAPPY CODING :)

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