2 repository-uri
Awesome GitHub RepositoriesMachine Learning Guides
Tutorials and guides specifically for applying a programming language to machine learning tasks.
Distinct from Python Programming Guides: Distinct from general programming guides by focusing on the application of Python to AI and data science specifically.
Explore 2 awesome GitHub repositories matching education & learning resources · Machine Learning Guides. Refine with filters or upvote what's useful.
Awesome Machine Learning Guides GitHub Repositories
Găsește cele mai bune repo-uri cu AI.Vom căuta cele mai potrivite repository-uri folosind AI.
- llsourcell/learn_machine_learning_in_3_months
llSourcell/Learn_Machine_Learning_in_3_Months
7,616Vezi pe GitHubThis project is a machine learning curriculum and educational course repository designed as a structured three-month study plan. It provides a guided path for mastering data science and artificial intelligence using the Python programming language. The repository organizes learning materials and code examples to cover mathematics, algorithms, and deep learning fundamentals. It uses a modular curriculum structure to break the domain into discrete monthly and weekly segments. The project functions as a curated resource map that aligns source code and notes with external instructional videos an
Provides a guided path for mastering data science and AI using the Python programming language.
- machinelearningmindset/machine-learning-course
machinelearningmindset/machine-learning-course
7,043Vezi pe GitHubThis project is a comprehensive educational curriculum for learning data science and predictive modeling using the Python programming language. It provides structured instructional material and guides covering supervised learning, unsupervised learning, and neural network design. The curriculum focuses on building, training, and evaluating machine learning models. It includes specific guides for implementing linear regression, decision trees, and support vector machines for predictive analysis, as well as tutorials on designing convolutional and recurrent neural network architectures. The co
Provides guides for applying Python to implement linear regression, decision trees, and support vector machines.
Python
