Download Python Machine Learning -all concepts a-z torrent

Python Machine Learning -all concepts a-z

Torrent:	Python Machine Learning -all concepts a-z
Description:	Python Machine Learning -all concepts a-z https://WebToolTip.com Published 4/2026 MP4 \| Video: h264, 1920x1080 \| Audio: AAC, 44.1 KHz, 2 Ch Language: English \| Duration: 2h 1m \| Size: 992.3 MB A Step-by-Step Guide from Basics to Advanced Machine Learning What you'll learn Understand the core concepts of Machine Learning and how algorithms learn from data Work with real datasets using NumPy and Pandas Build and train machine learning models using Scikit-learn Implement supervised and unsupervised learning algorithms Perform data preprocessing, feature scaling, and model evaluation Apply classification, regression, and clustering techniques Avoid common ML mistakes such as overfitting and underfitting Interpret model results and improve performance Requirements Basic knowledge of Python is helpful, but no prior Machine Learning experience is required. All ML concepts are explained from scratch in a simple and intuitive way.
Downloads:	76
Category:	Other /Tutorials
Size:	992.3 MB
Show Files »	[ WebToolTip.com ] Python Machine Learning -all concepts a-z Get Bonus Downloads Here.url (0.2 KB) ~Get Your Files Here ! 1 - Introduction to Machine Learning 1. Course Introduction.mp4 (38.6 MB) 2. What is Machine Learning.mp4 (7.0 MB) 3. ML vs Traditional Programming.mp4 (5.1 MB) 4. Supervised Learning.mp4 (4.1 MB) 5. Unsupervised Learning.mp4 (3.5 MB) 6. Reinforcement Learning.mp4 (4.0 MB) 10 - Feature Engineering 39. Encoding Categorical Variables.mp4 (21.6 MB) 40. Handling Outliers.mp4 (16.5 MB) 41. Feature Scaling.mp4 (26.2 MB) 42. Creating New Features.mp4 (20.9 MB) 11 - Saving & Loading Models 43. Model Persistence.mp4 (19.9 MB) 44. Training Phase.mp4 (19.6 MB) 45. Saving with Pickle.mp4 (10.2 MB) 46. Using Joblib.mp4 (8.0 MB) 47. Loading for Prediction.mp4 (28.3 MB) 12 - Practical ML Projects 48. Practical ML Project- Live Example.mp4 (35.7 MB) 13 - Deployment Basics 49. What is Model Deployment.mp4 (9.2 MB) 50. Deployment Workflow 1. Save Trained Model.mp4 (8.7 MB) 51. Deployment Workflow 2. Create API Endpoint.mp4 (1.4 MB) 52. Deployment Workflow 3. Test Integration.mp4 (5.4 MB) 53. Deployment Workflow 4. Deploy to Production.mp4 (4.8 MB) 54. Introduction to FastAPI for ML.mp4 (2.0 MB) 14 - Best Practices & ML Workflow 55. Project Structure.mp4 (6.5 MB) 56. Ethical ML & Privacy.mp4 (6.3 MB) 57. Reproducibility.mp4 (5.6 MB) 58. Data Versioning.mp4 (5.0 MB) 59. Code Quality Standards.mp4 (4.7 MB) 60. Documentation Essentials.mp4 (4.9 MB) 15 - Interview Preparation 61. Fundamental Concepts.mp4 (7.7 MB) 62. Algorithm Deep Dives.mp4 (4.3 MB) 63. Practical Scenarios & Coding Challenges.mp4 (7.6 MB) 64. Common Interview Topics & Final Tips.mp4 (7.8 MB) 2 - Python for Machine Learning 7. Why Python for ML.mp4 (5.4 MB) 8. Python ML Ecosystem.mp4 (17.1 MB) 9. Installation & Environment Setup with practical Demo.mp4 (28.4 MB) 3 - ML Libraries in Python 10. ML Libraries in Python.mp4 (10.6 MB) 11. NumPy Basics.mp4 (4.7 MB) 12. Pandas Basics.mp4 (3.8 MB) 13. Scikit-Learn basics.mp4 (3.5 MB) 14. Matplotlib & Seaborn basics.mp4 (3.4 MB) 15. SciPy basics.mp4 (2.7 MB) 4 - Data Handling & Preprocessing 16. Loading & Inspecting Data.mp4 (35.8 MB) 17. Handling Missing Values & Feature Engineering.mp4 (25.8 MB) 18. Train-Test Split & Scaling Normalization.mp4 (19.2 MB) 5 - Exploratory Data Analysis (EDA) 19. Understanding Your Data.mp4 (9.4 MB) 20. Summary Statistics.mp4 (10.7 MB) 21. Data Visualisation Basics.mp4 (19.3 MB) 22. Scatter Plots & Bar Charts.mp4 (13.4 MB) 23. Correlation Analysis.mp4 (19.1 MB) 24. Distribution Plots.mp4 (8.6 MB) 6 - Supervised Learning - Regression 25. Understanding Regression Simple Linear Regression & Multiple Linear Regression.mp4 (31.4 MB) 26. Model Training & Evaluation.mp4 (27.4 MB) 27. MAE(Mean Absolute Error), MSE(Mean Squared Error), RMSE(Root Mean Squared Error).mp4 (10.9 MB) 7 - Supervised Learning - Classification 28. Logistic Regression.mp4 (25.6 MB) 29. K-Nearest Neighbors.mp4 (36.6 MB) 30. Decision Trees.mp4 (15.7 MB) 31. Random Forest.mp4 (20.0 MB) 32. Model Evaluation Metrics Accuracy, Precision, Recall, F1 Score.mp4 (46.5 MB) 8 - Model Evaluation & Validation 33. Confusion Matrix.mp4 (55.3 MB) 34. Cross-Validation.mp4 (29.8 MB) 35. Overfitting, Underfitting, Bias-Variance Tradeoff.mp4 (23.6 MB) 9 - Unsupervised Learning 36. K-Means Clustering.mp4 (16.7 MB) 37. Hierarchical Clustering.mp4 (24.1 MB) 38. Principal Component Analysis.mp4 (26.6 MB) Bonus Resources.txt (0.1 KB) files
Added:	2026-04-17 03:36:27
Language:	English
Peers:	Seeders : 17 , Leechers : 25
Release name:	Python Machine Learning -all concepts a-z
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