A curated list of Machine learning videos, links, projects and datasets to help you conquer the ML landscape in 6 months
The goal of this level is to get you familiar with the ML universe. You will learn a bit of everything.
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1. Basics of Python - https://www.youtube.com/playlist?list=PLKnIA16_Rmvb1RYR-iTA_hzckhdONtSW4 2. OOP in Python - Lecture 1 - https://www.youtube.com/watch?v=1s869EfxoDo - Lecture 2 - https://www.youtube.com/watch?v=8To-A6VPL90 3. Advance Topics - File Handling - https://www.youtube.com/watch?v=ixEeeNjjOJ0 - Exception Handling - https://www.youtube.com/watch?v=NIWwJbo-9_8 - Regular Expressions - https://www.youtube.com/watch?v=K8L6KVGG-7o - Functional Programming - https://www.youtube.com/watch?v=SvK_GErE2nM - Basics of Flask - https://www.youtube.com/watch?v=swHI1H7DVsQ 4. Practice Problems - https://docs.google.com/document/d/1E_xCNijOWZ4Bm7r7DVj-1OA-oUopEFmv4tRm0YNuFWQ/edit?usp=sharing
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1. Numpy Playlist - https://www.youtube.com/watch?v=CpPLLp3snK4&list=PLKnIA16_Rmvb-ToL3RQ_bwxG4_ND-0-DT 2. Numpy Practice Problems - https://github.com/rougier/numpy-100
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1. Pandas Playlist - https://www.youtube.com/watch?v=kq9Vmg5d7Sk&list=PLKnIA16_RmvbR85fgbfVRKOiMokUKVupy 2. Pandas Problems - https://github.com/ajcr/100-pandas-puzzles
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1. Matplotlib - https://www.youtube.com/playlist?list=PL-osiE80TeTvipOqomVEeZ1HRrcEvtZB_ 2. Seaborn - https://www.youtube.com/playlist?list=PLKnIA16_RmvbB1bFGjvS6a8T0mnqawejo
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1. Statistics Playlist - https://www.youtube.com/watch?v=tPhzDKjQBpo&list=PLKnIA16_RmvbVrE0eZO2bCaFln6jaNq-1
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1. Playlist - https://www.youtube.com/watch?v=ZhacwtUR0SU&list=PLKnIA16_RmvZAqJzKstVHywcRNMn6pcGD
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1. Understanding your data - https://www.youtube.com/watch?v=mJlRTUuVr04 2. Univariate Analysis - https://www.youtube.com/watch?v=4HyTlbHUKSw 3. Bivariate and Multivariate Analysis - https://www.youtube.com/watch?v=6D3VtEfCw7w 4. Pandas Profiling - https://www.youtube.com/watch?v=E69Lg2ZgOxg 5. EDA on House Prices Dataset - https://www.kaggle.com/pmarcelino/comprehensive-data-exploration-with-python 6. EDA on Titanic Dataset - https://www.kaggle.com/startupsci/titanic-data-science-solutions 7. EDA on Haberman's Survival Dataset - https://www.kaggle.com/gokulkarthik/haberman-s-survival-exploratory-data-analysis 8. EDA on Heart Disease Dataset - https://www.kaggle.com/kralmachine/analyzing-the-heart-disease 9. EDA on IPL Dataset - https://www.kaggle.com/ash316/let-s-play-cricket 10. EDA on Wine Review Dataset - https://www.kaggle.com/kabure/wine-review-s-eda-recommend-systems 11. EDA on PIMA Diabetes Dataset - https://www.kaggle.com/shrutimechlearn/step-by-step-diabetes-classification-knn-detailed 12. EDA on Breast Cancer Dataset - https://www.kaggle.com/kanncaa1/statistical-learning-tutorial-for-beginners 13. EDA on Olympics Dataset - https://www.youtube.com/watch?v=5nQXhusiu7s 14. EDA on Covid Data - https://www.youtube.com/watch?v=ll0aZVNnOP8 15. WhatsApp Chat Analysis Project - https://www.youtube.com/watch?v=Q0QwvZKG_6Q
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1. What is Machine Learning? https://www.youtube.com/watch?v=ZftI2fEz0Fw 2. AI vs ML vs DL https://www.youtube.com/watch?v=1v3_AQ26jZ0 3. Types of Machine Learning - https://www.youtube.com/watch?v=81ymPYEtFOw 4. Batch Machine Learning - https://www.youtube.com/watch?v=nPrhFxEuTYU 5. Online Machine Learning - https://www.youtube.com/watch?v=3oOipgCbLIk 6. Instance based vs Model based learning - https://www.youtube.com/watch?v=ntAOq1ioTKo 7. Challenges in Machine Learning - https://www.youtube.com/watch?v=WGUNAJki2S4 8. Applications of Machine Learning - https://www.youtube.com/watch?v=UZio8TcTMrI 9. Machine Learning Development Lifecycle - https://www.youtube.com/watch?v=iDbhQGz_rEo 10. Data Engineer V Data Analyst V Data Scientist V ML Engineer - https://www.youtube.com/watch?v=93rKZs0MkgU 11. How to frame a Machine Learning problem? - https://www.youtube.com/watch?v=A9SezQlvakw 12. Installing and using software for data science - https://www.youtube.com/watch?v=82P5N2m41jE 13. How to work with CSV files? - https://www.youtube.com/watch?v=a_XrmKlaGTs 14. Working with JSON and SQL data - https://www.youtube.com/watch?v=fFwRC-fapIU 15. Building an End to End Machine Learning Project - https://www.youtube.com/watch?v=dr7z7a_8lQw
The goal of this level is to learn the core machine learning concepts and algorithms
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1. What are Tensors? - https://www.youtube.com/watch?v=vVhD2EyS41Y
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1. Covariance 2. Pearson Correlation Coefficient 3. QQ Plot 4. Confidence Interval 5. Hypothesis Testing 6. Chisquare Test, Anova Test 7. Playlist link - https://www.youtube.com/watch?v=qtaqvPAeEJY&list=PLKnIA16_Rmvbe9wDJGXc28KKr6lp5Jn2g
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1. Conditional Probability 2. Independent Events 3. Bayes Theorem 4. Uniform Distribution 5. Binomial Distribution 6. Bernaulli Distribution 7. Poission Distribution 8. Playlist Link - https://www.youtube.com/watch?v=Ty7knppVo9E&list=PLKnIA16_RmvYNbPMB6ofVLRCcTPUAftdY
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1. Representing Tabular Data 2. Vectors 3. Matrices 4. Matrix Multiplication 5. Dot Product 6. Equation of line in N-dim 7. Eigen Vector and Eigen Values 8. Playlist Link - https://www.youtube.com/watch?v=e9h-ZZ_ahRg&list=PLKnIA16_RmvYu0fS_RuIB2eTbJcTFdrAA
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1. Big Picture of Derivatives 2. Maxima and Minima 3. Playlist link - (first 4 videos only) https://www.youtube.com/playlist?list=PLBE9407EA64E2C318
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1. Linear Regression - https://www.youtube.com/watch?v=UZPfbG0jNec&list=PLKnIA16_Rmva-wY_HBh1gTH32ocu2SoTr 2. Gradient Descent - https://www.youtube.com/watch?v=ORyfPJypKuU&list=PLKnIA16_RmvZvBbJex7T84XYRmor3IPK1 3. Logistic Regression - https://www.youtube.com/watch?v=XNXzVfItWGY&list=PLKnIA16_Rmvb-ZTsM1QS-tlwmlkeGSnru 4. Support Vector Machines - https://www.youtube.com/watch?v=ugTxMLjLS8M&list=PLKnIA16_RmvbOIFee-ra7U6jR2oIbCZBL 5. Naive Bayes - https://www.youtube.com/watch?v=Ty7knppVo9E&list=PLKnIA16_RmvZ67wQaHoBuzXaDAfPz-a6l 6. K Nearest Neighbors - https://www.youtube.com/watch?v=BYaoDZM1IcU&list=PLKnIA16_RmvZiE-lEdN5RDi18-u-T43zd 7. Decision Trees - https://www.youtube.com/watch?v=gwgmSSTdiXs&list=PLKnIA16_RmvYGY_n9PP8zN-0LG9MoZRjU 8. Random Forest - https://www.youtube.com/watch?v=bHK1fE_BUms&list=PLKnIA16_RmvZyqP3WGUo7iVziIIea_1bp 9. Bagging - https://www.youtube.com/watch?v=LUiBOAy7x6Y&list=PLKnIA16_RmvZ7iKIcJrLjUoFDEeSejRpn 10. Adaboost - https://www.youtube.com/watch?v=sFKnP0iP0K0&list=PLKnIA16_RmvZxriy68dPZhorB8LXP1PY6 11. Gradient Boosting - https://www.youtube.com/watch?v=fbKz7N92mhQ&list=PLKnIA16_RmvaMPgWfHnN4MXl3qQ1597Jw 12. Xgboost - https://www.youtube.com/watch?v=BTLB-ppqBZc&list=PLKnIA16_RmvbXJbBW4zCy4Xbr81GRyaC4 13. Principle Component Analysis (PCA) - https://www.youtube.com/watch?v=ToGuhynu-No&list=PLKnIA16_RmvYHW62E_lGQa0EFsph2NquD 14. KMeans Clustering - https://www.youtube.com/watch?v=5shTLzwAdEc&list=PLKnIA16_RmvbA_hYXlRgdCg9bn8ZQK2z9 15. Heirarchical Clustering - https://www.youtube.com/watch?v=Ka5i9TVUT-E 16. DBSCAN - https://www.youtube.com/watch?v=RDZUdRSDOok 17. T-sne - https://www.youtube.com/watch?v=NEaUSP4YerM and https://distill.pub/2016/misread-tsne/
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Machine Learning Metrics - https://www.youtube.com/watch?v=Ti7c-Hz7GSM&list=PLKnIA16_RmvZJGOqRjqhOhTEmQW3vDdbQ
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Bias Variance Tradeoff - https://www.youtube.com/watch?v=74DU02Fyrhk
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Cross-Validation - https://www.youtube.com/watch?v=S5NkE-xgx98
The goal of this level is to get you introduced to the practical side of machine learning. What you learn at this level would really help you out there in the wild.
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1. Web Scraping - https://www.youtube.com/watch?v=8NOdgjC1988 * Project - Create a Pandas dataframe of Indian cuisines from some website using web scraping. 2. Fetch data from API - https://www.youtube.com/watch?v=roTZJaxjnJc * Project - Create a Pandas dataframe of movies from TMDB API.
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1. Complete Case Analysis - https://www.youtube.com/watch?v=aUnNWZorGmk 2. Handling missing numerical data - https://www.youtube.com/watch?v=mCL2xLBDw8M 3. Handling missing categorical data - https://www.youtube.com/watch?v=l_Wip8bEDFQ 4. Missing indicator - https://www.youtube.com/watch?v=Ratcir3p03w 5. KNN Imputer - https://www.youtube.com/watch?v=-fK-xEev2I8 6. MICE - https://www.youtube.com/watch?v=a38ehxv3kyk 7. Kaggle Notebooks and Practice Datasets - https://docs.google.com/document/d/1_9Y6kxNc6QTym2Y2JGEBbnCUbE1qZWLVzVXlT2eX_FQ/edit?usp=sharing
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1. Standarization - https://www.youtube.com/watch?v=1Yw9sC0PNwY 2. Normalization - https://www.youtube.com/watch?v=eBrGyuA2MIg
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1. Ordinal Enconding and Label Encoding - https://www.youtube.com/watch?v=w2GglmYHfmM 2. One Hot Encoding - https://www.youtube.com/watch?v=U5oCv3JKWKA 3. Encoding high cardinality categorical features - https://www.kaggle.com/general/16927 4. Feature hashing - https://datasciencestunt.com/dealing-with-categorical-features-with-high-cardinality-feature-hashing/
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1. Log Transform - https://www.youtube.com/watch?v=cTjj3LE8E90 2. Box Cox Transform - https://www.youtube.com/watch?v=lV_Z4HbNAx0 3. Yeo Johnson Transform - https://www.youtube.com/watch?v=lV_Z4HbNAx0 4. Discretization - https://www.youtube.com/watch?v=kKWsJGKcMvo
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1. Column Transformer - https://www.youtube.com/watch?v=5TVj6iEBR4I 2. Sklearn Pipelines - https://www.youtube.com/watch?v=xOccYkgRV4Q
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1. Working with time and date data - https://www.youtube.com/watch?v=J73mvgG9fFs
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1. What are Outliers? - https://www.youtube.com/watch?v=Lln1PKgGr_M 2. Outlier detection and removal using Z-score method - https://www.youtube.com/watch?v=OnPE-Z8jtqM 3. Outlier detection and removal using IQR method - https://www.youtube.com/watch?v=Ccv1-W5ilak 4. Percentile method - https://www.youtube.com/watch?v=bcXA4CqRXvM
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1. Feature Construction - https://www.youtube.com/watch?v=ma-h30PoFms
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1. Feature selection using SelectKBest and Recursive Feature Elimination - https://www.youtube.com/watch?v=xlHk4okO8Ls&t=1s 2. Chi-squared Feature Selection - https://www.youtube.com/watch?v=fMIwIKLGke0 3. Backward Feature Elimination - https://www.youtube.com/watch?v=zW1SvA0Z-l4&t=2s 4. Dropping features using Pearson correlation coefficient - https://www.youtube.com/watch?v=FndwYNcVe0U 5. Feature Importance using Random Forest - https://www.youtube.com/watch?v=R47JAob1xBY 6. Feature Selection Advise - https://www.youtube.com/watch?v=YaKMeAlHgqQ
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1. What is cross-validation? - https://www.youtube.com/watch?v=fSytzGwwBVw 2. Holdout Method - https://www.youtube.com/watch?v=4NnI3SBuww4 3. K-Fold Cross Validation - https://www.youtube.com/watch?v=gJo0uNL-5Qw 4. Leave 1 Out Cross Validation - https://www.youtube.com/watch?v=yxqcHWQKkdA 5. Time series cross validation - https://www.youtube.com/watch?v=g9iO2AwTXyI
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1. Stacking - https://www.youtube.com/watch?v=O-aDHBGMqXA 2. Blending - https://www.youtube.com/watch?v=TuIgtitqJho 3. LightGBM - https://www.youtube.com/watch?v=n_ZMQj09S6w 4. CatBoost - https://www.youtube.com/watch?v=8o0e-r0B5xQ
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1. GridSearchCV - https://www.youtube.com/watch?v=4Im0CT43QxY 2. RandomSearchCV - https://www.youtube.com/watch?v=Q5dH5mOQ_ik 3. Hyperparameter Tuning - https://www.youtube.com/watch?v=355u2bDqB7c
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1. How to handle imbalanced data - https://www.youtube.com/watch?v=JnlM4yLFNuo 2. Kaggle Notebook - https://www.kaggle.com/kabure/credit-card-fraud-prediction-rf-smote 3. SMOTE on Quora Dataset - https://www.kaggle.com/theoviel/dealing-with-class-imbalance-with-smote
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1. What is multicollinearity? - https://www.youtube.com/watch?v=ekuD8JUdL6M 2. Practical Example - https://www.youtube.com/watch?v=ATH4urDitI8 3. VIF in Multicollinearity - https://www.youtube.com/watch?v=GMAp_tP1ZQ0
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1. What is Data Leakage? - https://machinelearningmastery.com/data-leakage-machine-learning/ 2. Practical - Data Leakage on Quora Question Pair Dataset - https://www.kaggle.com/sudalairajkumar/simple-leaky-exploration-notebook-quora 3. Practical - Data Leakage on Credit Card data - https://www.kaggle.com/dansbecker/data-leakage
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1. Pickling your model - https://www.youtube.com/watch?v=yY1FXX_GSco 2. Flask Tutorial - https://www.youtube.com/watch?v=swHI1H7DVsQ 3. Streamlit Tutorial - https://www.youtube.com/watch?v=Klqn--Mu2pE 4. Deploy model on Heroku - https://www.youtube.com/watch?v=YncZ0WwxyzU 5. Deploy model on AWS - https://www.youtube.com/watch?v=_rwNTY5Mn40 6. Deploy model to GCP - https://www.youtube.com/watch?v=fw6NMQrYc6w 7. Deploy model to Azure - https://www.youtube.com/watch?v=qnbJcbjh-3s 8. ML model to Android App - https://www.youtube.com/watch?v=ax3WyB-_LJY
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1. What is Out of core ML? - https://www.youtube.com/watch?v=9e4nUuq2Hmg 2. Practical implementation of Out of core ML - https://www.youtube.com/watch?v=sRCuvcdvuzk 3. NYC Cab Dataset Project - https://vaex.io/blog/ml-impossible-train-a-1-billion-sample-model-in-20-minutes-with-vaex-and-scikit-learn-on-your
This is the level where you would dive into different domains of Machine Learning. Mastering these will make you a true Data Scientist.
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1. Complete SQL Roadmap - https://www.youtube.com/watch?v=FGBme8dWR_M 2. SQL learning resources - https://docs.google.com/document/d/1wCALgWubTOvuvlXJ3Eweh7AgJj4sPq2pW92y3viPZbs/edit?usp=sharing 3. The only video you need to see - https://www.youtube.com/watch?v=nopIGY1zJE0
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1. Movie Recommendation System - https://www.youtube.com/watch?v=1xtrIEwY_zY 2. Book Recommender System - https://www.youtube.com/watch?v=sf93xpq8vaA 3. Fashion Recommender System - https://www.youtube.com/watch?v=xanJe6e8Xuw
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1. Association Rule Mining(Apriori Algorithm) - https://www.youtube.com/watch?v=guVvtZ7ZClw 2. Eclat Algorithm - https://www.youtube.com/watch?v=oBiq8cMkTCU 3. Market Basket Analysis - https://www.youtube.com/watch?v=Y7Xkqqfz1UU
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1. Anamoly Detection Lecture from Microsoft Research - https://www.youtube.com/watch?v=12Xq9OLdQwQ 2. Novelty Detection Lecture - https://www.youtube.com/watch?v=vIDcjbpwY3k
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1. Complete NLP Roadmap - https://www.youtube.com/watch?v=PKv_okm1H-k 2. Complete NLP Playlist - https://www.youtube.com/watch?v=zlUpTlaxAKI&list=PLKnIA16_RmvZo7fp5kkIth6nRTeQQsjfX 3. NLP Project Ideas - https://www.youtube.com/watch?v=oWJe2T29kAo 4. Email Spam Classifier Project - https://www.youtube.com/watch?v=YncZ0WwxyzU 5. Building a Chatbot - https://www.youtube.com/watch?v=Nb21OhaW8GY
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Fundamentals of Neural Network - https://www.youtube.com/playlist?list=PLKnIA16_RmvYuZauWaPlRTC54KxSNLtNn
The objective of this level is to sharpen your knowledge that you have accumulated in the previous 4 levels
- 8 types of Projects for your portfolio - https://www.youtube.com/watch?v=SQHfry4xmdM
- How to select a project - https://www.youtube.com/watch?v=kH--k1VKFt4
- Car Price Predictor - https://www.youtube.com/watch?v=iRCaMnR_bpA
- Banglore House Price Predictor - https://www.youtube.com/watch?v=DVxkI1VmpCk
- Posture Detection using ML5.js - https://www.youtube.com/watch?v=kRvIcdLhDtU
- Laptop Price Predictor - https://www.youtube.com/watch?v=BgpM2IiCH6k
- Which bollywood celebrity are you? - https://www.youtube.com/watch?v=X67rclJcIL0
- Finding similar GOT characters - https://www.youtube.com/watch?v=ygGknomFEWY
- IPL win probability predictor - https://www.youtube.com/watch?v=ygGknomFEWY
- T20 score predictor - https://www.youtube.com/watch?v=ygGknomFEWY
- Titanic Survivor Prediction - https://www.youtube.com/watch?v=Bnp94fpxZjY
- Diabetes Prediction using ML - https://www.youtube.com/watch?v=xUE7SjVx9bQ
- Fake news prediction - https://www.youtube.com/watch?v=nacLBdyG6jE
- Loan Status Prediction - https://www.youtube.com/watch?v=XckM1pFgZmg
- Gold Price Prediction - https://www.youtube.com/watch?v=9ffkBvh8PTQ
- Handwriting Classifier - https://www.youtube.com/watch?v=1B3YIkyPNk0
- Flight Fare Prediction - https://www.youtube.com/watch?v=y4EMEpEnElQ
- Link for 500 ML DL projects - https://github.com/ashishpatel26/500-AI-Machine-learning-Deep-learning-Computer-vision-NLP-Projects-with-code