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Master Machine Learning from fundamentals to advanced techniques through 19 comprehensive chapters. This path covers 316 carefully curated problems spanning linear algebra, probability, classical ML, deep learning, reinforcement learning, and more.
This comprehensive learning path covers 316 problems across 19 chapters, taking you from mathematical foundations to advanced ML techniques. **Learning Path Structure:** • Chapters 1-2: Mathematical Foundations - Linear algebra and probability • Chapter 3: Data Preprocessing - Feature engineering and data pipelines • Chapter 4: Calculus & Optimization - Gradients and optimization theory • Chapter 5-6: Classical ML - Traditional algorithms and evaluation metrics • Chapters 7-8: Neural Networks - Fundamentals and training techniques • Chapters 9-11: Deep Learning - CNNs, RNNs, and Transformers • Chapters 12-14: Advanced Topics - Modern architectures and RL • Chapters 15-18: Applications - NLP, CV, LLM evaluation, and MLOps Each chapter builds on previous concepts for a cohesive learning experience.
Linear Transformation Vector
Matrix Transpose
Matrix Dimension Restructuring
Matrix Axis Mean Computation
Matrix Scalar Multiplication
Spectral Analysis Square Matrix
Similarity Matrix Transform
Matrix Inverse 2x2
Matrix Product Multiplication
Iterative Linear System Solver
Jacobi Singular Value Decomposition
Determinant 4x4 Laplace Expansion
Kernel Support Vector Classifier
Basis Change Matrix
Singular Value Decomposition 2x2
Vector To Diagonal Matrix
Correlation Matrix Computation
Row Reduced Canonical Form
Scaled Dot Product Attention
Iterative Linear System Solver
Gaussian Elimination Linear Solver
Term Frequency Inverse Document Frequency
Cg Linear System Solver
Csr Sparse Matrix Conversion
Vector Projection Onto Line
Column Compressed Sparse Matrix
Column Space Basis Extraction
Binary Classification Outcome Matrix
Vector Angular Similarity Measure
Vector Inner Product
Polynomial Basis Expansion
Orthonormal Basis Computation
Three Dimensional Vector Cross Product
Determinant Based System Solver
Component Wise Vector Addition
Motion Vector Endpoint Error
Classification Outcome Matrix Builder
Matrix Determinant Trace Calculator
Orthogonal Triangular Factorization
Gradient Field Matrix Computation
Gradient Vector Computation
Second Order Curvature Matrix
Softmax Jacobian Matrix
Gaussian Kernel Similarity Matrix
Gradient Vector Analysis
Hessian Critical Point Classifier