Practical AI for Everyone

Empowering you to use machine learning to get valuable insights from data.

🎓 No computer science or math degrees required.
🤖 Learn when to use specific ML techniques for your meaningful tasks.
🔥 Implement basic ML algorithms and deep neural networks with PyTorch.
🖥️ Run everything on the browser without any set up using Google Colab.


00. Notebooks

Introduction to Google Colaboratory notebooks.

01. Python

Basics of the Python programming language.

02. NumPy

Numpy basics for scientific computing.

03. Pandas

Pandas analysis tool for data processing.

04. Linear Regression

Linear regression with Scikit-learn using SGD.

05. Logistic Regression

Logistic regression with Scikit-learn using SGD.

06. Random Forests

Basics of decision trees and random forests.

07. PyTorch

PyTorch library to build dynamic neural networks.

08. Multilayer Perceptron

Basics of MLPs in PyTorch.

09. Data and Models

Importance of data quality and quantity for modeling.

10. Object Oriented ML

A simple neural network with functions and classes.

11. Convolutional NNs

Basics of CNNs for text processing.

12. Embeddings

Learning and using embeddings for representing text.

13. Recurrent NNs

Basics of RNNs for sequence processing.

14. Advanced RNNs

Advanced topics with RNNs.

15. Computer Vision

Basics of computer vision using CNNs.

Coming soon!

Topics on CV, NLP, RL, GANS/CVAE, transfer learning, recsys, etc.


Working on something cool and think I could help? I'd love to collaborate with you on topics ranging from AI research to product development.

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About me

My name is Goku Mohandas and I'm an AI researcher in Silicon Valley. My expertise is in AI research and production with a focus on natural language processing. Reach out if you have any AI questions, suggestions, or just want to say hi 👋

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