لغة الآلة | Elgouhary AI

Elgouhary AI

Elgouhary AI

هنا نهتم بتعلم مجالات الذكاء الاصطناعي وتعلم الآلة والتعلم العميق بكل فروعه النظرية والعملية من خلال البرمجة بلغة البايثون وسيتم تغطية كل ما يخص مجال الـ Data Science & Data Analysis وهيكون من خلال الادوات المختلفة لتحقيق ذلك من Excel, Tableau, Power BI, SPSS, SAS وغيرها من الادوات. أرجو منكم صالح الدعاء .

تفاصيل الكورس

  • دروس الكورس47
  • مدة الكورس16س 0د
  • عدد الطلاب2
  • اللغةعربي
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دروس الكورس

  1. 1 | #1 What is Machine Learning 00:06:01
  2. 2 | Machine Learning Supervised Learning 00:16:06
  3. 3 | Machine Learning Unsupervised Learning 00:07:18
  4. 4 | Simple Linear Regression Model 00:07:44
  5. 5 | Machine Learning Linear Regression Cost Function 00:08:22
  6. 6 | Machine Learning Linear Regression Cost Function for One Parameter 00:19:35
  7. 7 | Machine Learning Linear Regression Cost Function for Two Parameters 00:14:08
  8. 8 | Machine Learning Linear Regression Gradient Descent Overview 00:08:08
  9. 9 | Machine Learning Linear Regression Gradient Descent Mathematically 00:12:05
  10. 10 | Machine Learning Gradient Descent for Linear Regression 00:15:46
  11. 11 | Machine Learning Multiple Linear Regression Model 00:09:45
  12. 12 | Machine Learning Multiple Linear Regression Model Feature Scaling 00:13:18
  13. 13 | Machine Learning Checking Gradient Descent for Conversions Choosing the learning rate 00:09:02
  14. 14 | Machine Learning Feature Engineering Polynomial Regression 00:07:26
  15. 15 | Machine Learning Linear Regression vs. Classification 00:06:25
  16. 16 | Machine Learning Logistic Regression 00:07:23
  17. 17 | Machine Learning Decision Boundary 00:08:16
  18. 18 | Machine Learning Cost Function for Logistic Regression 00:17:29
  19. 19 | Machine Learning Overfitting and Underfitting 00:08:47
  20. 20 | Machine Learning How to prevent Overfiting 00:09:29
  21. 21 | Machine Learning Cost Function with Regularization 00:11:31
  22. 22 | Machine Learning Gradient Descent with Regularization 00:08:33
  23. 23 | Machine Learning Introduction to Neural Networks 00:10:07
  24. 24 | Machine Learning Neural Networks in details 00:14:42
  25. 25 | Machine Learning Neural Networks Activation Functions 00:14:55
  26. 26 | Multi-class Classification softmax Regression Multi-Lable Classification 00:17:09
  27. 27 | Machine Learning Advanced Optimization Adam algorithm 00:06:10
  28. 28 | Machine Learning Machine Learning Diagnostic Evaluating The Model 00:14:13
  29. 29 | Machine Learning Model Selection 00:12:17
  30. 30 | Machine Learning Bias and Variance 00:10:24
  31. 31 | Machine Learning Regularization with Bias and Variance 00:08:14
  32. 32 | Machine Learning A Baseline Level of Performance Learning Curves 00:16:00
  33. 33 | Machine Learning Improving The Learning Algorithm 00:12:43
  34. 34 | Machine Learning Introduction to Decision Trees 00:08:21
  35. 35 | Machine Learning Decision Tree Learning Process 00:11:23
  36. 36 | Machine Learning Decision Tree Measuring Purity Entropy Information Gain 00:17:53
  37. 37 | Machine Learning Building a Decision Tree Model 00:08:08
  38. 38 | #38 Machine Learning Decision Tree Using one hot encoding of categorical features 00:05:58
  39. 39 | #39 Machine Learning Decision Tree Continuous Valued Features 00:12:28
  40. 40 | #40 Machine Learning Decision Tree Regression Trees 00:09:11
  41. 41 | #41 Machine Learning Decision Tree Sampling with replacement Random Forest Algo. XGBoost 00:15:09
  42. 42 | #42 Machine Learning Decision Trees vs Neural Networks 00:03:01
  43. 43 | #43 Unsupervised Learning Clustering K-means Intuition 00:11:09
  44. 44 | #44 Unsupervised Learning Anomaly Detection Finding Unusual Events 00:10:08
  45. 45 | #45 Unsupervised Learning Principle Component Analysis PCA 00:07:37
  46. 46 | #46 Machine Learning Introduction to The Reinforcement Learning 00:07:52
  47. 47 | الأساسيات النظرية لتعلم الآلة كاملة في فيديو واحد Machine Learning Complete Course 07:42:49
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    29-07-2024
    تعلم الآلة بالعربي Machine Learning in Arabic

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