Machine Learning Fundamentals A Python-Based Course - Printable Version +- Softwarez.Info - Software's World! (https://softwarez.info) +-- Forum: Library Zone (https://softwarez.info/Forum-Library-Zone) +--- Forum: Video Tutorials (https://softwarez.info/Forum-Video-Tutorials) +--- Thread: Machine Learning Fundamentals A Python-Based Course (/Thread-Machine-Learning-Fundamentals-A-Python-Based-Course--696078) |
Machine Learning Fundamentals A Python-Based Course - AD-TEAM - 11-28-2024 4.2 GB | 00:30:14 | mp4 | 1920X1080 | 16:9 Genre:eLearning |Language:English
Files Included :
001 Course Overview (69.36 MB) 001 Lesson 1 1 Biggest Milestones in AI History (77.14 MB) 002 Lesson 1 2 Artificial Intelligence Principles (90.33 MB) 001 Lesson 2 1 Introduction to the Mathematical Principles of Machine Learning (154.08 MB) 002 Lesson 2 2 Vectors (126.46 MB) 003 Lesson 2 3 Matrices Basics (170.21 MB) 004 Lesson 2 4 Matrices Decomposition (104.27 MB) 001 Lesson 3 1 Introduction to the Statistical Principles of Machine Learning (127.49 MB) 002 Lesson 3 2 Probability Distributions (116.83 MB) 003 Lesson 3 3 Descriptive Statistics Basics for Machine Learning - Measures of Central Tendency (108.8 MB) 004 Lesson 3 4 Descriptive Statistics Basics for Machine Learning - Measures of Dispersion (117.23 MB) 005 Lesson 3 5 Statistical Inference and Modeling Basics (129.3 MB) 001 Lesson 4 1 Supervision in Machine Learning (165.77 MB) 002 Lesson 4 2 Introduction to Feature Engineering (161.73 MB) 003 Lesson 4 3 Intro to Regression and Regression Metrics (99.35 MB) 004 Lesson 4 4 Linear Regression Basics - Closed-form solution (129.73 MB) 005 Lesson 4 5 Linear Regression Basics - Multivariate Regression (69.68 MB) 006 Lesson 4 6 Linear Regression in Python - Simple and Multivariate Regression (125.4 MB) 007 Lesson 4 7 Linear Regression in Python - Testing the Assumptions (141.76 MB) 008 Lesson 4 8 Intro to Classification (56.71 MB) 009 Lesson 4 9 Classification Metrics (146.58 MB) 010 Lesson 4 10 Class Imbalance Problems (153.74 MB) 011 Lesson 4 11 Logistic Regression Basics (111.54 MB) 012 Lesson 4 12 Decision Trees Basics (156.68 MB) 013 Lesson 4 13 Supervised Learning in Python (194.05 MB) 014 Lesson 4 14 Introduction to Hyperparameter Optimization (163.64 MB) 001 Lesson 5 1 Unsupervised Machine Learning (106.81 MB) 002 Lesson 5 2 Clustering Basics (62 MB) 003 Lesson 5 3 k-Means Clustering (141.44 MB) 004 Lesson 5 4 Principal Component Analysis (PCA) Basics (119.91 MB) 005 Lesson 5 5 Unsupervised Learning in Python (163.25 MB) 001 Lesson 6 1 Introduction to Natural Language Processing (NLP) (133.5 MB) 002 Lesson 6 2 Text Representation Methods - Part 1 Bag-of-Words & N-Grams (104.49 MB) 003 Lesson 6 3 Text Representation Methods - Part 2 TF-IDF Method (123.61 MB) 004 Lesson 6 4 Text Representation Methods - Part 3 Word Embeddings (76.88 MB)] Screenshot
Fikper
FileAxa RapidGator TurboBit |