March 1, 2024
Courses
Famous courses by Andrew Ng that are highly recommended for understanding the basics and advanced concepts:
Data Science and Machine Learning Tutorials
YouTube Videos
Introduction to Statistics
Explore statistics through these resources:
Sample Projects
Practice with these engaging sample projects:
Books
- An Introduction to Statistical Learning: with Applications in R
- Hands-on Machine Learning with Scikit-learn, Keras & TensorFlow
Useful Websites
Important Keywords to Learn
Master these essential concepts:
- Time-series Analysis, Gradient Descent, Bagging, Boosting
- Information Gain, Entropy, Gini Impurity, Cost Function
Python Resources
Introduction
Reading CSV Files
Types of Charts and Plots
Pandas Tutorials
Additional Courses
Broaden your knowledge with these courses:
Python Libraries to Know
- Numpy, Scikit-learn, TensorFlow, PyTorch
Mini-Projects to Start
Begin with these beginner-friendly projects:
-
- House Prediction – Linear Regression
- Decision Tree Classification
- Random Forest Classification
- House Prediction – Linear Regression
- Decision Tree Classification
- Random Forest Classification
- SVM Classifier
- MINST Handwritten SVM
- Compare 5 Algorithms
- Spam or Not Classification
- Face Detector CNN
- Hyperparameters using Grid Search CV
- RNN and LSTM for Time Series
- Tensor Playground
- Facial Feature Detection using Dlib
- AlexNet
- Object Detection using YOLO
- Reinforcement Learning
- NLP
- Stock Market Prediction using LSTM
- ML Project Examples
Polina ViolaMarch 7, 2024
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