Machine-Learning-Specialization-Coursera and deep-learning-specialization
These are complementary repositories covering different specializations in the same learning path—the Machine Learning Specialization provides foundational ML concepts while the Deep Learning Specialization builds advanced neural network techniques on top of them, so learners typically work through both sequentially.
About Machine-Learning-Specialization-Coursera
greyhatguy007/Machine-Learning-Specialization-Coursera
Contains Solutions and Notes for the Machine Learning Specialization By Stanford University and Deeplearning.ai - Coursera (2022) by Prof. Andrew NG
Organizes three specialization courses into structured Jupyter notebooks covering linear/logistic regression, neural networks, and unsupervised learning with hands-on labs implementing algorithms using NumPy, scikit-learn, and TensorFlow. Each week includes practice quizzes, optional labs demonstrating core concepts (gradient descent, vectorization, feature scaling), and graded programming assignments with complete solutions. The implementation emphasizes vectorized NumPy operations and comparison between manual gradient descent implementations and scikit-learn's optimized solvers.
About deep-learning-specialization
greyhatguy007/deep-learning-specialization
Contains Solutions to Deep Learning Specailization - Coursera
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