Why learn Machine Learning ❓ #
- With machine learning, you can build applications that can learn and improve from experience without being explicitly programmed, enabling them to make predictions, identify patterns, and automate tasks.
- Some cool examples of machine learning applications include,
- Speech recognition used in virtual assistants like Siri and Alexa
- Movies and series recommender systems used by streaming platforms like Netflix
- Object detection used in self driving cars
🎓 Take Away Skills #
After completing this learning path you will be able to:
- Build machine learning projects
🛠️ Prerequisites #
🧑🏻💻 Programming Knowledge #
Programming knowledge in python is a must. There is no point in continuing without programming knowledge.
You can use Python learning path to learn python :snake:
💡 Machine learning involves mathematics.
An interest in mathematics and knowledge in +2 level mathematics would be good.
📲 Installation and Setup #
- A laptop windows/mac is a must.
- Would prefer a laptop with NVIDIA GPU or an M1 Mac
- A light weight code editor like VSCode
- Should install python. Rest of the packages you can install on the go.
💡 Learning Session #
Basics of A.I. #
🎓 Topics to Learn
- Difference between machine learning and normal programming
- What is A.I., Machine Learning and Deep learning
- Supervised, Non-supervised, reinforcement and self-supervised learning
- A.I. Ethics and practices
- Training, testing and inference
Video tutorials
- Difference between software engineering and machine learning engineering by Mustafa from google
- Intro to Machine learning by tensorflow team
- A.I., ML and DL by google developers
- Types of Machine learning models by google developers
- AI & Ethics by code.org
Articles/Blogs
- Where to use machine learning by amazon
- Trianing vs Testing KDNuggets
- Medium article about where not to use machine learning by Cassie Kozyrkov
🛠️ Get into action
- Dig more in the internet about the above topics and learn
- Write blogs/ do youtube videos about your learning
- Take sessions about the above topics
Machine learning algorithms #
🎓 Topics to Learn
- Linear Regression
- Logistic Regression
- Decision Trees
- Random Forest
- Naive Bayes
- k-Nearest Neighbors (k-NN)
- Support Vector Machines (SVM)
- Gradient Boosting
- Neural Networks
Video Tutorials
- Playlist by Sentdex about classic machine learning algorithms
- Sci-kit learn crash course by free code camp
📄 Articles/Blogs
🛠️ Get into action
- Follow Sentdex tutrials, understand machine learning algorithms and implement it in python
- Learn sklearn and try out the code in free code camp crash course
- Pick up a dataset and train a model using just python and then use sklearn
Deep learning and neural networks #
🎓 Topics to Learn
- What is deep learning
- Deep neural networks
- Vision, NLP, Time series...etc
- Gradient descent
- Types of neural networks
- Convolutional Neural networks
- Recurrent Neural networks
- Transformers
- GAN
Video Tutorials
- Explanation of CNN by codebasics
- Building a CNN by Sentdex
- Transformers Playlist by code emporium
- How stable diffusion and DALL-E works by computerphile
- How GAN works by computerphile
📄 Articles/Blogs
- Neural Networks and deep learning by Micheal Nielson
- A neural network in 11 lines of code by Andrew Trask
- Gradient Descent tutorial by Andrew Trask
- What is NLP by Machine learning mastery
- Everything you want to know about computer vision by towards data science
- LSTM RNN by Andrew Trask
🛠️ Get into action
- Write a blog or create a youtube video about your learning
- Try out the codes in the above resources yourself
Learn machine learning framework(s) #
🎓 Topics to Learn
- Different machine learning frameworks
- Tensorflow, Keras, Pytorch, fastAI, huggingface transformers, spacy...etc
- MNIST image classification in 3 popular ML frameworks
- Use framework docs and learn
- Do projects
Video Tutorials
- Various machine learning frameworks by Smitha Kolan
- Tensorflow 2.0 by freecodecamp
- Pytorch by freecodecamp
📄 Articles/Blogs
🛠️ Get into action
- Go through the above resources. Try out code
- Think about a machine learning project (or ask chatGPT for ideas) and start doing it with your learning
🚀 Project Pool #
- Build a chatbot using spacy and huggingface transformers to talk about this learning paths
- Collect dataset for indian dishes and create a food classifier app that explain various food items in India.
- Build a malayalam fake news classifier by fine tuning a huggingface transformer model
Created with 💙 by Gopikrishan Sasikumar & TinkerHub