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مشین لرننگ اردو میں: لمز فال 2021 (آغا علی رضا)

از Agha Ali Raza - Youtube Channel

کورس کی زبان
کورس کی زبان: اردو
سطح
درمیانی
دورانیہ
77 اسباق · 43.5 گھنٹے

آپ کیا کر سکیں گے

  • سپروائزڈ لرننگ کا ڈھانچہ اور ہر ماڈل کی حدود سمجھا سکیں
  • کنفیوژن میٹرکس، ایف اسکور اور آر او سی سے ماڈل جانچ سکیں
  • لینیئر ریگریشن، ٹری اور بوسٹنگ سمجھ کر استعمال کر سکیں
  • پی سی اے سے ڈائمینشنز کم کر سکیں

اس کورس کے بارے میں

لمز میں ریکارڈ کیا گیا یونیورسٹی کا مکمل مشین لرننگ کورس، اردو/ہندی میں: 77 لیکچرز، تقریباً 43 گھنٹے۔ سپروائزڈ لرننگ، کے این این، کنفیوژن میٹرکس، آر او سی، لینیئر ریگریشن، ڈیسیژن ٹری، بوسٹنگ اور پی سی اے، سب ریاضی کے ساتھ۔ یونیورسٹی طلبہ اور سنجیدہ سیکھنے والوں کے لیے۔

شروع کرنے سے پہلے: بنیادی پرابیبلٹی، لینیئر الجبرا اور پروگرامنگ

نصاب

77 اسباق · کل 43:27:50

  1. 1[Machine Learning in Urdu/Hindi] 001- Introduction to Machine Learning -W1L2-HQ1:09:48
  2. 2[Machine Learning in Urdu/Hindi] 002 - Supervised Learning setup -00-W2L1-HQ55:14
  3. 3[Machine Learning in Urdu/Hindi] 002- Supervised Learning setup -01-W2L2-HQ1:09:29
  4. 4[Machine Learning in Urdu/Hindi] 003-01- K-Nearest Neighbors (KNN) Introduction -W3L1-HQ41:19
  5. 5[Machine Learning in Urdu/Hindi] 003-02- K-Nearest Neighbors (KNN) Distances -W3L1-HQ20:49
  6. 6[Machine Learning in Urdu/Hindi] 003-03- K-Nearest Neighbors (KNN) Algorithm -W3L1-HQ31:03
  7. 7[Machine Learning in Urdu/Hindi] 003-04- K-Nearest Neighbors (KNN) Error Bounds -W3L2-HQ23:18
  8. 8[Machine Learning in Urdu/Hindi] 003-05- K-Nearest Neighbors (KNN) Enhancements -W3L2-HQ39:31
  9. 9[Machine Learning in Urdu/Hindi] 003-06- K-Nearest Neighbors (KNN) Curse of Dimensionality -W3L2-HQ37:37
  10. 10[Machine Learning in Urdu/Hindi] 004-01- The Confusion Matrix -W4L112:03
  11. 11[Machine Learning in Urdu/Hindi] 004-02- ML Performance Metrics -W4L135:22
  12. 12[Machine Learning in Urdu/Hindi] 004-03- The F-Score -W4L18:06
  13. 13[Machine Learning in Urdu/Hindi] 004-04- Multiclass Classification -W4L1_Corrected24:50
  14. 14[Machine Learning in Urdu/Hindi] 004-05- The making of Gold (ML Gold Labels) -W4L226:07
  15. 15[Machine Learning in Urdu/Hindi] 004-06- Which Mean? -W4L220:56
  16. 16[Machine Learning in Urdu/Hindi] 004-07- ROC, AUC, EER -W4L2-W5L157:13
  17. 17[Machine Learning in Urdu/Hindi] 005-00- Linear Regression: Motivation for Linearity -W5L17:17
  18. 18[Machine Learning in Urdu/Hindi] 005-01- Lines, Planes, Hyperplanes, Vectors, n-dimensions -W5L150:41
  19. 19[Machine Learning in Urdu/Hindi] 005-02- Linear Regression -W5L118:30
  20. 20[Machine Learning in Urdu/Hindi] 005-03- Linear Regression Setup -W5L125:37
  21. 21[Machine Learning in Urdu/Hindi] 005-04- Gradient Descent -W5L241:13
  22. 22[Machine Learning in Urdu/Hindi] 005-05- Multivariate Linear Regression -W5L224:10
  23. 23[Machine Learning in Urdu/Hindi] 005-06- Multivariate Gradient Descent for Linear Regression -W5L25:08
  24. 24[Machine Learning in Urdu/Hindi] 005-07- Linear Regression in Practice -W5L215:58
  25. 25[Machine Learning in Urdu/Hindi] 005-08- Polynomial Regression -W6L13:41
  26. 26[Machine Learning in Urdu/Hindi] 005-09- Overfitting, Bias, Variance -W6L130:49
  27. 27[Machine Learning in Urdu/Hindi] 005-10- Linear Regression: Choosing Features -W6L115:43
  28. 28[Machine Learning in Urdu/Hindi] 005-11- Regression: Regularization -W6L130:27
  29. 29[Machine Learning in Urdu/Hindi] 006-00- Logistic Regression -W6L230:59
  30. 30[Machine Learning in Urdu/Hindi] 006-01- Logistic Regression: Decision Boundary -W6L226:57
تمام 77 اسباق دکھائیں
  1. 31[Machine Learning in Urdu/Hindi] 006-02- Logistic Regression: Cost Function -W6L230:56
  2. 32[Machine Learning in Urdu/Hindi] 006-03-Logistic Regression: Gradient Descent -W7L27:15
  3. 33[Machine Learning in Urdu/Hindi] 006-04- Logistic Regression: Multiclass -W7L222:17
  4. 34[Machine Learning in Urdu/Hindi] 006-05-Logistic Regression: Hardmax and Softmax -W7L220:05
  5. 35[Machine Learning in Urdu/Hindi] 007-00- The Bayes Theorem: Introduction and Derivation -W7L226:51
  6. 36[Machine Learning in Urdu/Hindi] 007-01- The Bayes Theorem: Examples and MAP -W8L126:41
  7. 37[Machine Learning in Urdu/Hindi] 007-02- Bayes: Worked Examples (Supplementary Lecture) -W8L157:32
  8. 38[Machine Learning in Urdu/Hindi] 007-03- Generative and Discriminative Classifiers -W8L123:04
  9. 39[Machine Learning in Urdu/Hindi] 008-01- Classification using Naive Bayes -W8L139:36
  10. 40[Machine Learning in Urdu/Hindi] 008-02- NaiveBayes: Under the Hood 01 -W8L236:42
  11. 41[Machine Learning in Urdu/Hindi] 008-03- Naive Bayes: Under the Hood 02 -W8L224:27
  12. 42[Machine Learning in Urdu/Hindi] 008-04- Naive Bayes: Text Generation -W8L235:27
  13. 43[Machine Learning in Urdu/Hindi] 008-05- Naive Bayes: Gaussian -W9L138:42
  14. 44[Machine Learning in Urdu/Hindi] 008-06- Naive Bayes: Decision Boundary -W9L17:35
  15. 45[Machine Learning in Urdu/Hindi] 008-07- Naive Bayes: Pros and Cons -W9L111:05
  16. 46[Machine Learning in Urdu/Hindi] 009-01- Hypothesis Spaces -W9L115:15
  17. 47[Machine Learning in Urdu/Hindi] 009-02- Frequentist Viewpoint -W9L126:22
  18. 48[Machine Learning in Urdu/Hindi] 009-03- Bayesian Viewpoint -W9L116:30
  19. 49[Machine Learning in Urdu/Hindi] 009-04- Bayes Optimal Classifier -W9L133:32
  20. 50[Machine Learning in Urdu/Hindi] 010-01- Perceptron Introduction -W9L244:49
  21. 51[Machine Learning in Urdu/Hindi] 010-02- Perceptron: Learning Algorithm -W9L223:09
  22. 52[Machine Learning in Urdu/Hindi] 010-03- Perceptron Algorithm: Proof of Convergence -W10L136:54
  23. 53[Machine Learning in Urdu/Hindi] 011-00- SVM Overview -W10L131:26
  24. 54[Machine Learning in Urdu/Hindi] 011-01- Linear SVMs (Hard Margin) -W10L247:56
  25. 55[Machine Learning in Urdu/Hindi] 011-02- Linear SVMs (Soft Margin) -W10L221:09
  26. 56[Machine Learning in Urdu/Hindi] 012-001- Neural Networks: Introduction and Overview -W11L11:21:03
  27. 57[Machine Learning in Urdu/Hindi] 012-002- Neural Networks: Notation and Forward Pass -W11L242:51
  28. 58[Machine Learning in Urdu/Hindi] 012-003- Activation Functions -W11L218:51
  29. 59[Machine Learning in Urdu/Hindi] 012-004- Training the NN: Forward and Backward Passes -W12L150:04
  30. 60[Machine Learning in Urdu/Hindi] 013-001- Decision Trees: KD Trees -W12L235:36
  31. 61[Machine Learning in Urdu/Hindi] 013-002- Decision Trees: Tree Terminology -W12L247:16
  32. 62[Machine Learning in Urdu/Hindi] 013-003- Decision Trees: Introduction and Usage -W12L255:57
  33. 63[Machine Learning in Urdu/Hindi] 013-004- Decision Trees: Training -W13L157:20
  34. 64[Machine Learning in Urdu/Hindi] 013-005- Decision Trees: Pros and Cons -W13L140:53
  35. 65[Machine Learning in Urdu/Hindi] 013-006_ Decision Trees: Entropy and Cross-Entropy -W13L258:18
  36. 66[Machine Learning in Urdu/Hindi] 013-007- Huffman Coding -W13L210:14
  37. 67[Machine Learning in Urdu/Hindi] 013-008- Parametric vs Non-Parametric ML Methods -W13L25:16
  38. 68[Machine Learning in Urdu/Hindi] 014-001- Generalization Error Decomposition: Bias, Variance - W14L145:54
  39. 69[Machine Learning in Urdu/Hindi] 014-002- Bagging -W14L159:34
  40. 70[Machine Learning in Urdu/Hindi] 014-003- Random Forests -W14L241:06
  41. 71[Machine Learning in Urdu/Hindi] 016-001- Unsupervised Learning -W16L135:06
  42. 72[Machine Learning in Urdu/Hindi] 016-002- Unsupervised Learning: K-Means -W16L11:18:57
  43. 73[Machine Learning in Urdu/Hindi] 016-003- Unsupervised Learning: Hierarchical Clustering -W16L240:57
  44. 74LUMSx Machine Learning Certification2:32
  45. 75011 Unsupervised Learning PCA1:21:29
  46. 76010 Boosting54:59
  47. 77009--Decision Trees-01-Training Strengths Weaknesses58:25

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ویڈیوز Agha Ali Raza - Youtube Channel کی، ان کے آفیشل یوٹیوب چینل سے۔ یوٹیوب پر سبسکرائب کریں

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