Learn Machine Learning Community

About

I believe one thing which is learning by sharing. I learned a lot from the community and this is the time I should give it back. So I started a community to share my knowledge regarding machine learning and related domains. This community has around 250000+ ML enthusiasts who are willing to learn. Because of this community, I learned a lot and shared a lot.

You can find my community on Linkedin, Instagram, Telegram, Youtube.

We do accept donations (mail me to learn more about this) which can help us to manage things. Thank you.

Content

Artificial Intelligence

  1. What The F*ck is AI
  2. All You Need To Know About Artificial Intelligence
  3. Arificial Intelligence Applications
  4. Learn How Machines Learn
  5. Artificial Intelligence For Social Good
  6. Biased Artificial Intelligence
  7. Difference Between AI/ ML/ DS/ DL
  8. Doing Crimes Using Arificial Intelligence
  9. Is Your Job At Rist Because Of AI
  10. What If AI Takes Over The World
  11. When Artificial Intelligence Fails
  12. When Artificial Intelligence Meets Internet Of Things (IoT)
  13. Learn How AI Makes Us Social Media Addictive

Data Preprocessing

  1. 10+ Data Visualization Techniques
  2. Build Your Know Word2vec Using Gensim
  3. Data Augmentation Techniques Using Tensorflow
  4. Things To Keep In Mind While Collecting Data
  5. Different Things To Do in Data PreProcessing Step
  6. Dealing With Categorical Data
  7. Different Encoding Techniques For Categorical Data
  8. Feature Scaling
  9. Fixing Imbalanced Dataset
  10. Handling Missing Data
  11. Lemmatization And Stemming
  12. Learn More About Outliers
  13. Remove Stop Words
  14. Test, Train, Validation Dataset
  15. Learn More About TF-IDF
  16. Treating Imbalanced Data
  17. Treating Missing Values
  18. What EDA Techniques For What
  19. Why Data Cleaning Is So Important

Data Science

  1. Data Science Project LifeCycle
  2. Data Science Project Steps
  3. Data Science Skillset
  4. Data Science Toolkit
  5. Data Scientist Skills
  6. Every Data Scientist Should Know All These
  7. Find A Data Science Mentor
  8. Different Job Roles In Data Science
  9. Most Popular Data Science Programs and Courses
  10. Statistician vs Data Scientist
  11. Steps Involved In A Data Science Project
  12. The Data Science Of Hierarchy Of Needs
  13. Beginner Mistakes To Avoid As A Data Scientist
  14. What Does Really Data Scientists Do
  15. Top Data Science Usecases
  16. Mistakes To Avoid As a Data Scientist
  17. You Should Not Become A Data Scientist

Deep Learning

  1. What The F*ck Is Deep Learning
  2. Why Deep Learning
  3. What is Artificial Neural Networks
  4. What Is A Perceptron
  5. What Is Multi Layered Perceptron
  6. Learn How Feed Forward Network Works
  7. Limitations Of Perceptrons
  8. Dropout Methods For Deep Learning
  9. Simple Introduction To GANS
  10. Deep Learning Applications
  11. How To Hack Neural Networks
  12. Best Deep Learning Laptops
  13. NLP Pipeline
  14. Different Sota Models And Datasets
  15. Spend Less Time On Data Annotation

Deep Learning Applications

  1. Convert Images To Toonify Images
  2. Detect Deep Fake Videos
  3. Learn How Machine Translation Works
  4. Learn How Object Detection Works
  5. Convert Black And White Images To Color
  6. Convert Images To Cartoon Using White Box Cartoonization
  7. Learn How Facial Recognition Works
  8. Learn How Human Pose Estimation Works
  9. Learn How Text To Speech Works
  10. Technical Guide to GPT-3
  11. Text Classification Using BERT
  12. Create Images From Text Using OpenAI DALL-E

Interview Questions

  1. 100+ Machine Learning Interview Questions And Answers
  2. 10 Best Coding Websites
  3. 10 Most Asked Puzzles In A Data Science Interview
  4. 1 Page Resume For Data Science
  5. Mistakes To Avoid During Interviews
  6. Ace Data Science Hackathons
  7. Best Websites To Find Data Science Jobs
  8. Data Structures And Algorithms
  9. Get An Interview Opeertunity Through Linkedin
  10. Get A Job At Top MNCs PArt - 1
  11. Get A Job At Top MNCs PArt - 2
  12. Google Data Science Interview Questions
  13. Most Asked Data Science And Algorithms Interview Questions
  14. Reasons For Failing In Machine Learning Interviews
  15. Tips For Data Science Jobs
  16. Why Machine Learning Courses Fails To GEt You A Job

Learning Paths

  1. Data Scientist Path
  2. Machine Learning Path
  3. Computer Vision Path
  4. Deep Learning Path
  5. Path To Become A Machine Learning Expert
  6. Self Taught Data Scientist

Machine Learning Algorithms

  1. What The F*ck Is Machine Learning
  2. 11 Machine Learning Algorithms You Should Know
  3. Learn How Machine Learning Algorithms Works
  4. Machine Learning Algorithms
  5. Machine Learning Algorithms Explained In 10 Minutes
  6. Linear Regression In Detail
  7. Logistic Regression In Detail
  8. Naive Bayes In Detail
  9. Polynomial Regression
  10. Support Vector Machines In Detail
  11. K Nearest Neighbors In Detail
  12. Decision Trees In Detail
  13. Random Forest In Detail
  14. Gradient Boost In Detail
  15. XGBoost In Detail
  16. Stacking Ensembles In Detail
  17. Light Gradient Boosting In detail
  18. CatBoost In Detail
  19. Cascading Ensemble In Detail
  20. Adaboost In Detail
  21. K Means Clustering In detail
  22. K Means + + In Detail
  23. K Medoids In Detail
  24. Hierarchical Clustering In Detail
  25. DBScan In Detail
  26. Learn How To Approach Any Machine Learning Problem
  27. Machine Learning Algorithms Expectations
  28. Machine Learning Terms You Should Know
  29. Next Big Thing In Machine Learning

Machine Learning Important Things

  1. 38+ Performance Metrics
  2. 9 Machine Learning End To End Project Steps
  3. Machine Learning Academia vs Industry
  4. Machine Learning In Browser Using TensorFlow JS
  5. Best And Worst Cases Of MAchine Learning Algorithms
  6. Bias Variance Tradeoff
  7. Data Leakage In Machine Learning
  8. Different Loss Functions
  9. Different Performance Metrics
  10. Machine Learning Without Data
  11. Different Methods To Avoid Overfitting
  12. Model Performance on Test And Train Data
  13. Steps To Consider While Applying Machine Learning Algorithms
  14. What Is Loss Function
  15. Different Distance Measures In Machine Learning
  16. Feature Scaling In Machine Learning (Normalization And Standardization
  17. Increase Your Dataset Size
  18. Fit And Evaluate All Machine Learning Models In One Line Of Code
  19. Starting your First Machine Learning Project

Machine Learning Miscellaneous

  1. 2 Different Ways To Learn Machine Learning
  2. 5 Different Types Of Learning
  3. 9 Machine Learning End To End Project Steps
  4. Learn How Google Is Using Machine Learning
  5. Why Machine Learning For CyberSecurity
  6. Different Types Of Learning Algorithms
  7. End To End Project Steps
  8. Learn How Facebook Is Using Machine Learning
  9. Learn How PubG Is Using Machine Learning
  10. Machine Learning In Your Everyday Life
  11. Main Challenges Of Machine Learning
  12. Online Learning And Batch Learning
  13. Stay Focused On Learning Machine Learning Everyday
  14. Tips For Beginners To Learn Machine Learning
  15. What Is Statistical Learning
  16. What Makes A Good Machine Learning Engineer
  17. When To Use Machine Learning
  18. Learn How AI Is Used For Web Development
  19. Learn How Machine Learning Is Used In Astronomy
  20. Learn How Machine Learning Can Help Women
  21. Why Python For Machine Learning

Math

  1. Why Probability And Statistics Are Important
  2. Dimensionality Reduction
  3. Calculus
  4. Curse Of Dimensionality
  5. Gradient Descent
  6. Linear Algebra
  7. Math For Data Science
  8. PCA In Detail
  9. Statistics And Probability
  10. T-SNE In Detail
  11. Why Linear Algebra For Machine Learning
  12. What is Dimensionality Reduction

Project Ideas

  1. 50 Python Project Ideas
  2. AI ML Startup Ideas
  3. Build A Perfect AI Based Project
  4. Computer Vision Project Ideas
  5. GANS Based Project Ideas
  6. Mobile APP Ideas Using Machine Learning
  7. Project Ideas With Code Part - 1
  8. Project Ideas With Code Part - 2
  9. Python Project Ideas

Learning Resources

  1. 100 Days Of Machine Learning Code With Resources
  2. 100 Days Of Deep Learning Code With Resources
  3. 5 Free Courses To Learn Deep Learning
  4. 5 Free Courses To Learn NLP
  5. 8 Best Python Books
  6. Top Resources To Follow
  7. Complete Machine Learning Resources
  8. Dataset Search Engines
  9. Machine Learning Javascript Libraries
  10. Must Read Data Science Books
  11. My Favourite Free Learning Resources
  12. Python Libraries For Robotics
  13. Top Deep Learning Frameworks
  14. Top Math Related Youtube Channels
  15. Most Popular Machine Learning Courses

Miscellaneous

  1. Avoid These Coding Mistakes
  2. How To Buy Or Build A Perfect Laptop
  3. Why Competitive Programming
  4. Creating Tensors With TensorFlow
  5. Datasets Released By Google
  6. Everything About AutoML
  7. Get Started With OpenSource
  8. Google Dataset Search Engine
  9. How To Start Programming
  10. Jupyter Notebook Tips And Tricks
  11. Keras vs TensorFlow
  12. Start Your Kaggle Journey
  13. Top Masters Programs In Machine Learning
  14. Why Kaggle
  15. Must Have Jupyter Notebook Extensions

Model Deployment

  1. Deploy ML Models On Heroku Using Flask
  2. Save Machine Learning Models

MLOPS

  1. Learn How A/B Testing Works
  2. Difference Between DevOps And MLOps
  3. Introduction To Machine Learning Operations (MLOPS)
  4. Machine Learning LifeCycle
  5. This Is Why Machine Learning Models Fails In Production
  6. Learn How To Build Machine Learning Pipelines
  7. Track All Your Machine Learning Models Using MLFOW

Social channels

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Followers Count - 9600+

Subscribers Count - 2800+