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- 【影视】 Trans500-Hub-I Kill It TS-Learning A Lesson with Beatriz-28-06-24-Hd
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Trans500 Hub- I Kill It TS-Learning A Lesson with Beatriz.mp4 3.9 GB
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- 【影视】 Trans500.24.06.27.Beatriz.Oliveira.Learning.A.Lesson.with.Beatriz.XXX.1080p.MP4-Narcos[XC]
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narcos-ts5-24-06-27-beatriz-oliveira-learning-a-lesson-with-beatriz-1080p.mp4 3.9 GB
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- 【影视】 IKillitts.com - Beatriz Oliveira - Learning A Lesson with Beatriz (kill409), 27.06.2024_1080p.mp4
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IKillitts.com - Beatriz Oliveira - Learning A Lesson with Beatriz (kill409), 27.06.2024_1080p.mp4 3.9 GB
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- 【影视】 [Tutorialsplanet.NET] Udemy - Hyperparameter Optimization for Machine Learning
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6. Bayesian Optimization/6. Sequential Model-Based Optimization.mp4 119.6 MB
8. Scikit-Optimize/13. Optimizing Hyperparameters of a CNN.mp4 116.8 MB
6. Bayesian Optimization/16. Scikit-Optimize - Neuronal Networks.mp4 116.8 MB
7. Other SMBO Algorithms/2. SMAC Demo.mp4 104.4 MB
6. Bayesian Optimization/12. Scikit-Optimize - 1-Dimension.mp4 101.9 MB
9. Hyperopt/3. Search space configuration and distributions.mp4 98.6 MB
10. Optuna/6. Optimizing hyperparameters of a CNN.mp4 89.4 MB
6. Bayesian Optimization/8. Multivariate Gaussian Distribution.mp4 88.0 MB
6. Bayesian Optimization/11. Acquisition Functions.mp4 86.3 MB
5. Basic Search Algorithms/9. Random Search with Hyperopt.mp4 85.1 MB
4. Cross-Validation/2. Cross-Validation schemes.mp4 83.7 MB
6. Bayesian Optimization/9. Gaussian Process.mp4 79.9 MB
10. Optuna/8. Evaluating the search with Optuna's built in functions.mp4 74.5 MB
6. Bayesian Optimization/5. Bayes Rule.mp4 71.1 MB
9. Hyperopt/7. Optimizing multiple ML models simultaneously.mp4 69.8 MB
4. Cross-Validation/3. Estimating the model generalization error with CV - Demo.mp4 69.0 MB
9. Hyperopt/5. Search algorithms.mp4 68.0 MB
3. Performance metrics/5. Creating your own metrics.mp4 67.6 MB
10. Optuna/4. Search algorithms.mp4 66.6 MB
2. Hyperparameter Tuning - Overview/1. Parameters and Hyperparameters.mp4 65.3 MB
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- 【影视】 Learning.To.Love.Again.2020.P.WEB-DL.72Op.mkv
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Learning.To.Love.Again.2020.P.WEB-DL.72Op.mkv 3.9 GB
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- 【影视】 [GigaCourse.Com] Udemy - Machine Learning with SciKit-Learn with Python
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9. Cross Validation/13. Performance Analysis on the Test Set.mp4 125.2 MB
6. Pandas/6. Remove Operations.mp4 123.1 MB
9. Cross Validation/5. PCA Pipeline.mp4 122.9 MB
9. Cross Validation/1. Cross Validation.mp4 117.4 MB
5. Matlplotlib/3. Multiple Figures and Subplots.mp4 115.7 MB
8. Learning and Predicting/4. Persisting Models.mp4 110.3 MB
9. Cross Validation/3. K-Means Clustering Example.mp4 109.0 MB
6. Pandas/7. Pandas Arithmetic Operations.mp4 108.2 MB
6. Pandas/4. Data Structure in Pandas Continue.mp4 107.1 MB
8. Learning and Predicting/5. K-NN Algorithm with Example.mp4 106.3 MB
3. NumPy Array/6. Numpy Array Splicing.mp4 103.6 MB
3. NumPy Array/4. NumPy Array Operations Continue.mp4 97.5 MB
9. Cross Validation/15. Language Identifcation.mp4 97.4 MB
9. Cross Validation/9. Text Data Example.mp4 94.2 MB
3. NumPy Array/8. Stacking Together Different Arrays.mp4 89.7 MB
5. Matlplotlib/2. Understanding Various Functions of Pyplot.mp4 89.6 MB
9. Cross Validation/14. Parameter Tuning.mp4 89.3 MB
6. Pandas/3. Data Structure in Pandas.mp4 88.0 MB
6. Pandas/5. Pandas Column Select.mp4 83.4 MB
3. NumPy Array/3. NumPy Array Operations.mp4 82.3 MB
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- 【影视】 [ FreeCourseWeb.com ] Udemy - Machine Learning with SciKit-Learn with Python
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~Get Your Files Here !/9. Cross Validation/13. Performance Analysis on the Test Set.mp4 125.2 MB
~Get Your Files Here !/6. Pandas/6. Remove Operations.mp4 123.1 MB
~Get Your Files Here !/9. Cross Validation/5. PCA Pipeline.mp4 122.9 MB
~Get Your Files Here !/9. Cross Validation/1. Cross Validation.mp4 117.4 MB
~Get Your Files Here !/5. Matlplotlib/3. Multiple Figures and Subplots.mp4 115.7 MB
~Get Your Files Here !/8. Learning and Predicting/4. Persisting Models.mp4 110.3 MB
~Get Your Files Here !/9. Cross Validation/3. K-Means Clustering Example.mp4 109.0 MB
~Get Your Files Here !/6. Pandas/7. Pandas Arithmetic Operations.mp4 108.2 MB
~Get Your Files Here !/6. Pandas/4. Data Structure in Pandas Continue.mp4 107.1 MB
~Get Your Files Here !/8. Learning and Predicting/5. K-NN Algorithm with Example.mp4 106.3 MB
~Get Your Files Here !/3. NumPy Array/6. Numpy Array Splicing.mp4 103.6 MB
~Get Your Files Here !/3. NumPy Array/4. NumPy Array Operations Continue.mp4 97.5 MB
~Get Your Files Here !/9. Cross Validation/15. Language Identifcation.mp4 97.4 MB
~Get Your Files Here !/9. Cross Validation/9. Text Data Example.mp4 94.2 MB
~Get Your Files Here !/3. NumPy Array/8. Stacking Together Different Arrays.mp4 89.7 MB
~Get Your Files Here !/5. Matlplotlib/2. Understanding Various Functions of Pyplot.mp4 89.6 MB
~Get Your Files Here !/9. Cross Validation/14. Parameter Tuning.mp4 89.3 MB
~Get Your Files Here !/6. Pandas/3. Data Structure in Pandas.mp4 88.0 MB
~Get Your Files Here !/6. Pandas/5. Pandas Column Select.mp4 83.4 MB
~Get Your Files Here !/3. NumPy Array/3. NumPy Array Operations.mp4 82.3 MB
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- 【影视】 [FreeCourseSite.com] Udemy - Machine Learning with SciKit-Learn with Python
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9. Cross Validation/13. Performance Analysis on the Test Set.mp4 125.2 MB
6. Pandas/6. Remove Operations.mp4 123.1 MB
9. Cross Validation/5. PCA Pipeline.mp4 122.9 MB
9. Cross Validation/1. Cross Validation.mp4 117.4 MB
5. Matlplotlib/3. Multiple Figures and Subplots.mp4 115.7 MB
8. Learning and Predicting/4. Persisting Models.mp4 110.3 MB
9. Cross Validation/3. K-Means Clustering Example.mp4 109.0 MB
6. Pandas/7. Pandas Arithmetic Operations.mp4 108.2 MB
6. Pandas/4. Data Structure in Pandas Continue.mp4 107.1 MB
8. Learning and Predicting/5. K-NN Algorithm with Example.mp4 106.3 MB
3. NumPy Array/6. Numpy Array Splicing.mp4 103.6 MB
3. NumPy Array/4. NumPy Array Operations Continue.mp4 97.5 MB
9. Cross Validation/15. Language Identifcation.mp4 97.4 MB
9. Cross Validation/9. Text Data Example.mp4 94.2 MB
3. NumPy Array/8. Stacking Together Different Arrays.mp4 89.7 MB
5. Matlplotlib/2. Understanding Various Functions of Pyplot.mp4 89.6 MB
9. Cross Validation/14. Parameter Tuning.mp4 89.3 MB
6. Pandas/3. Data Structure in Pandas.mp4 88.0 MB
6. Pandas/5. Pandas Column Select.mp4 83.4 MB
3. NumPy Array/3. NumPy Array Operations.mp4 82.3 MB
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9. Cross Validation/13. Performance Analysis on the Test Set.mp4 125.2 MB
6. Pandas/6. Remove Operations.mp4 123.1 MB
9. Cross Validation/5. PCA Pipeline.mp4 122.9 MB
9. Cross Validation/1. Cross Validation.mp4 117.4 MB
5. Matlplotlib/3. Multiple Figures and Subplots.mp4 115.7 MB
8. Learning and Predicting/4. Persisting Models.mp4 110.3 MB
9. Cross Validation/3. K-Means Clustering Example.mp4 109.0 MB
6. Pandas/7. Pandas Arithmetic Operations.mp4 108.2 MB
6. Pandas/4. Data Structure in Pandas Continue.mp4 107.1 MB
8. Learning and Predicting/5. K-NN Algorithm with Example.mp4 106.3 MB
3. NumPy Array/6. Numpy Array Splicing.mp4 103.6 MB
3. NumPy Array/4. NumPy Array Operations Continue.mp4 97.5 MB
9. Cross Validation/15. Language Identifcation.mp4 97.4 MB
9. Cross Validation/9. Text Data Example.mp4 94.2 MB
3. NumPy Array/8. Stacking Together Different Arrays.mp4 89.7 MB
5. Matlplotlib/2. Understanding Various Functions of Pyplot.mp4 89.6 MB
9. Cross Validation/14. Parameter Tuning.mp4 89.3 MB
6. Pandas/3. Data Structure in Pandas.mp4 88.0 MB
6. Pandas/5. Pandas Column Select.mp4 83.4 MB
3. NumPy Array/3. NumPy Array Operations.mp4 82.3 MB
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- 【影视】 [FreeCourseSite.com] Udemy - Learn Machine Learning Maths Behind
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1. Prerequisite Machine Learning Basic and Introduction With Naive Bayes/1. Machine Learning ( Algorithms) Types - Part 1.mp4 101.8 MB
1. Prerequisite Machine Learning Basic and Introduction With Naive Bayes/1. Machine Learning ( Algorithms) Types - Part 1.vtt 4.8 kB
1. Prerequisite Machine Learning Basic and Introduction With Naive Bayes/10. Naive Bayes Graphical Proof.mp4 227.3 MB
1. Prerequisite Machine Learning Basic and Introduction With Naive Bayes/10. Naive Bayes Graphical Proof.vtt 9.8 kB
1. Prerequisite Machine Learning Basic and Introduction With Naive Bayes/11. Expert System With Naive Bayes.mp4 226.4 MB
1. Prerequisite Machine Learning Basic and Introduction With Naive Bayes/11. Expert System With Naive Bayes.vtt 10.5 kB
1. Prerequisite Machine Learning Basic and Introduction With Naive Bayes/2. Machine Learning ( Algorithms) Types - Part 2.mp4 200.8 MB
1. Prerequisite Machine Learning Basic and Introduction With Naive Bayes/2. Machine Learning ( Algorithms) Types - Part 2.vtt 9.4 kB
1. Prerequisite Machine Learning Basic and Introduction With Naive Bayes/3. 5 Types of Different Problems Which Can be Solved With Machine Learning.mp4 150.7 MB
1. Prerequisite Machine Learning Basic and Introduction With Naive Bayes/3. 5 Types of Different Problems Which Can be Solved With Machine Learning.vtt 7.4 kB
1. Prerequisite Machine Learning Basic and Introduction With Naive Bayes/4. Machine Learning Algorithms and Why It Matters.mp4 43.8 MB
1. Prerequisite Machine Learning Basic and Introduction With Naive Bayes/4. Machine Learning Algorithms and Why It Matters.vtt 2.1 kB
1. Prerequisite Machine Learning Basic and Introduction With Naive Bayes/5. Rating Machine Learning Algorithms.mp4 153.2 MB
1. Prerequisite Machine Learning Basic and Introduction With Naive Bayes/5. Rating Machine Learning Algorithms.vtt 7.6 kB
1. Prerequisite Machine Learning Basic and Introduction With Naive Bayes/6. Algorithms We are Going to Cover and What They Can Do.mp4 154.3 MB
1. Prerequisite Machine Learning Basic and Introduction With Naive Bayes/6. Algorithms We are Going to Cover and What They Can Do.vtt 8.0 kB
1. Prerequisite Machine Learning Basic and Introduction With Naive Bayes/7. Starting With Naive Bayes.mp4 115.3 MB
1. Prerequisite Machine Learning Basic and Introduction With Naive Bayes/7. Starting With Naive Bayes.vtt 5.5 kB
1. Prerequisite Machine Learning Basic and Introduction With Naive Bayes/8. How Naive Bayes Works and Proof.mp4 134.1 MB
1. Prerequisite Machine Learning Basic and Introduction With Naive Bayes/8. How Naive Bayes Works and Proof.vtt 6.0 kB
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- 【影视】 [OneHack.Us] Edureka.co - Applied Machine Learning With Python 2025
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03-Association_Rule_Mining_And_Recommendation_System/01-Association_Rules/03-demonstrating_apriori_algorithm.mp4 91.9 MB
02-Machine_Learning_Algorithms/02-Svm_Knn_And_Naive_Bayes_Algorithms/02-terminologies_in_svm.mp4 90.4 MB
02-Machine_Learning_Algorithms/02-Svm_Knn_And_Naive_Bayes_Algorithms/03-hinge_loss_function_and_other_parameters.mp4 86.8 MB
02-Machine_Learning_Algorithms/01-Decision_Tree_And_Random_Forest/04-step_by_step_building_of_decision_tree.mp4 81.6 MB
01-Introduction_To_Machine_Learning/03-Regression/03-calculating_ols.mp4 79.1 MB
02-Machine_Learning_Algorithms/02-Svm_Knn_And_Naive_Bayes_Algorithms/08-example_of_naive_bayes_algorithm.mp4 78.5 MB
03-Association_Rule_Mining_And_Recommendation_System/03-Reinforcement_Learning_And_Boosting/10-demonstration_of_boosting_building_a_model.mp4 76.8 MB
02-Machine_Learning_Algorithms/02-Svm_Knn_And_Naive_Bayes_Algorithms/05-demonstration_of_svm_setting_up_the_svm_classifier.mp4 71.3 MB
02-Machine_Learning_Algorithms/01-Decision_Tree_And_Random_Forest/07-demonstration_building_decision_tree_and_random_forest.mp4 66.7 MB
02-Machine_Learning_Algorithms/01-Decision_Tree_And_Random_Forest/02-what_is_decision_tree.mp4 66.7 MB
03-Association_Rule_Mining_And_Recommendation_System/03-Reinforcement_Learning_And_Boosting/12-demonstration_of_k_means_clustering.mp4 64.1 MB
02-Machine_Learning_Algorithms/03-Dimensionality_Reduction/04-eigen_values_and_eigen_vectors.mp4 62.3 MB
01-Introduction_To_Machine_Learning/04-Evaluation_Metrics/02-example_for_calculating_confusion_matrix.mp4 61.4 MB
02-Machine_Learning_Algorithms/03-Dimensionality_Reduction/09-demonstration_of_lda.mp4 61.4 MB
01-Introduction_To_Machine_Learning/04-Evaluation_Metrics/04-overfitting_and_underfitting.mp4 60.3 MB
02-Machine_Learning_Algorithms/03-Dimensionality_Reduction/01-dimensionality_reduction.mp4 60.2 MB
01-Introduction_To_Machine_Learning/03-Regression/14-demonstration_of_logistic_regression_transforming_data.mp4 60.1 MB
03-Association_Rule_Mining_And_Recommendation_System/02-Recommendation_Engines/03-demonstration_of_recommendation_engine_preparing_data.mp4 59.5 MB
03-Association_Rule_Mining_And_Recommendation_System/03-Reinforcement_Learning_And_Boosting/03-demonstration_of_boosting_cleaning_and_transforming_dataset.mp4 59.0 MB
02-Machine_Learning_Algorithms/03-Dimensionality_Reduction/08-working_of_lda.mp4 58.2 MB
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- 【影视】 A.New.Female.Teacher.Is.Used.As.A.Learning.Material.Sex.Education.At.A.Boys.School.Decensored.Roshy.Jav.Japan.Japanese.Asian.Decensored.Handjob.Creampie.Humiliation.FemaleTeacher.BigTits.Teacher.School.MORE.DECENSORED.HD.JAV.PORN.WWW.ROSHY.TV.mp4
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A.New.Female.Teacher.Is.Used.As.A.Learning.Material.Sex.Education.At.A.Boys.School.Decensored.Roshy.Jav.Japan.Japanese.Asian.Decensored.Handjob.Creampie.Humiliation.FemaleTeacher.BigTits.Teacher.School.MORE.DECENSORED.HD.JAV.PORN.WWW.ROSHY.TV.mp4 3.9 GB
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- 【影视】 [CourseClub.ME] Udacity - Machine Learning Engineer Nanodegree v2.0.0
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Part 02-Module 04-Lesson 02_Deep Q-Learning/07. Experience Replay-wX_-SZG-YMQ.mp4 50.7 MB
Part 02-Module 04-Lesson 03_Policy-Based Methods/07. M2L3 07 V2-ZBLLGIN1EfU.mp4 45.7 MB
Part 01-Module 11-Lesson 04_Gaussian Mixture Models and Cluster Validation/19. MLND - Unsupervised Learning - L3 20 Internal Validation Indices MAIN V1 V2-39JruOTptKI.mp4 42.7 MB
Part 02-Module 04-Lesson 02_Deep Q-Learning/10. DQN Improvements-Zfdbp93A2GU.mp4 41.3 MB
Part 02-Module 03-Lesson 05_Monte Carlo Methods/03. MC Prediction State Values-0q2wSWyuBj8.mp4 35.0 MB
Part 02-Module 04-Lesson 01_RL in Continuous Spaces/01. Deep Reinforcement Learning-GPjK124RU5g.mp4 34.8 MB
Part 01-Module 11-Lesson 04_Gaussian Mixture Models and Cluster Validation/09. MLND - Unsupervised Learning - L3 09 Expectation Maximization Pt 1 V1 MAIN 1 V2-cf-RLKn5ubA.mp4 34.2 MB
Part 02-Module 06-Lesson 02_Take 30 Min to Improve your LinkedIn/02. Meet Chris-0ccflD9x5WU.mp4 34.1 MB
Part 02-Module 04-Lesson 03_Policy-Based Methods/02. M2L3 02 V2-ToS8vXGdODE.mp4 34.1 MB
Part 01-Module 13-Lesson 01_PCA/31. Eigenfaces Code-LgLYw-G4sLQ.mp4 34.0 MB
Part 01-Module 11-Lesson 04_Gaussian Mixture Models and Cluster Validation/14. MLND - Unsupervised Learning - L3 15 GMM Examples And Applications MAIN V2 V1-FRoxeLp81Bg.mp4 33.2 MB
Part 02-Module 03-Lesson 04_Dynamic Programming/14. Policy Improvement-4_adUEK0IHg.mp4 31.9 MB
Part 02-Module 03-Lesson 06_Temporal-Difference Methods/03. TD Prediction TD(0)-CsD6b0csU7o.mp4 31.6 MB
Part 02-Module 04-Lesson 01_RL in Continuous Spaces/11. Linear Function Approximation-OJ5wrB7o-pI.mp4 30.1 MB
Part 02-Module 03-Lesson 04_Dynamic Programming/05. An Iterative Method-AX-hG3KvwzY.mp4 28.9 MB
Part 01-Module 01-Lesson 01_Welcome to Machine Learning/01. 01 Boas-vindas ao programa IntroduçãoMLND V3-A8AnsR6e75I.mp4 28.3 MB
Part 01-Module 10-Lesson 05_Support Vector Machines/13. SVM 11 Polynomial Kernel 3 V1-XmbK8OjbX5U.mp4 28.1 MB
Part 01-Module 11-Lesson 04_Gaussian Mixture Models and Cluster Validation/10. MLND - Unsupervised Learning - L3 10 Expectation Maximization Pt 2 MAIN V1 V2-B_xXd0mFUm4.mp4 27.6 MB
Part 02-Module 04-Lesson 02_Deep Q-Learning/06. Deep Q Network-GgtR_d1OB-M.mp4 26.9 MB
Part 02-Module 06-Lesson 01_Optimize Your GitHub Profile/14. Interview with Art - Part 3-M6PKr3S1rPg.mp4 26.3 MB
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- 【影视】 SolidWorks Complete Learning Tutorials
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27SolidWorks 2014 Tutorial 27- Extrude Cut, insert sketch, convert, select body.mp4 70.2 MB
9SolidWorks 2014 Tutorial 9- Spline, Types, using and dimensioning.mp4 57.4 MB
10SolidWorks 2014 Tutorial 10- Ellipse Menu.mp4 51.5 MB
73SolidWorks 2014 Surface Tutorial 73- Guided Loft Surface, 3D sketch.mp4 51.4 MB
113 SolidWorks Assembly Tutorial- Inserting and positioning components.mp4 50.6 MB
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145 SolidWorks Drawing Tutorial- BOM and Balloons.mp4 44.6 MB
71SolidWorks 2014 Surface Tutorial 71- Swept and Twist surface.mp4 43.3 MB
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114 SolidWorks Assembly Tutorial- Mating, Concident mate.mp4 41.6 MB
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46SolidWorks 2014 Tutorial 46- Circular Pattern, Sloty disk.mp4 38.9 MB
87SolidWorks 2014 Surface Tutorial 87- Trim Surface.mp4 38.6 MB
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- 【影视】 Learning to Learn [Efficient Learning] Zero to Mastery
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[TutsNode.com] - Learning to Learn [Efficient Learning] Zero to Mastery/06 The Techniques/090 Method of Loci.mp4 137.8 MB
[TutsNode.com] - Learning to Learn [Efficient Learning] Zero to Mastery/01 Introduction/004 Exercise_ Method of Loci.mp4 137.7 MB
[TutsNode.com] - Learning to Learn [Efficient Learning] Zero to Mastery/01 Introduction/001 Course Outline.mp4 137.1 MB
[TutsNode.com] - Learning to Learn [Efficient Learning] Zero to Mastery/05 The Science/046 Short And Long Term Memory.mp4 118.9 MB
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~Get Your Files Here !/7. K-Nearest Neighbors Classifier (KNN)/8. Project Develop a KNN machine model in Python codes.mp4 544.5 MB
~Get Your Files Here !/8. Naive Bayes Classifier/4. Project Develop a Naive Bayes machine model in Python codes.mp4 281.2 MB
~Get Your Files Here !/9. Logistic Regression Classifier/5. Project Develop a Logistic Regression machine model in Python codes.mp4 275.1 MB
~Get Your Files Here !/6. Support Vector Machine (SVM) Classifier/11. Project Develop a support vector machine model in Python.mp4 268.1 MB
~Get Your Files Here !/3. Principal Component Analysis (PCA)/4. Understand PCA mathematically by solving an example of covariance matrix.mp4 246.3 MB
~Get Your Files Here !/8. Naive Bayes Classifier/3. Solve an example to cement the concept of Bayes rule.mp4 204.8 MB
~Get Your Files Here !/10. Decision Tree Classifier/3. Project Develop a Decision Tree machine model in Python codes.mp4 177.8 MB
~Get Your Files Here !/7. K-Nearest Neighbors Classifier (KNN)/6. Euclidean distance formula to measure the distance between two data points.mp4 156.2 MB
~Get Your Files Here !/3. Principal Component Analysis (PCA)/2. How principal component analysis works Check it graphically.mp4 81.7 MB
~Get Your Files Here !/8. Naive Bayes Classifier/2. Understand Naive Bayes rule by giving a daily life example.mp4 77.0 MB
~Get Your Files Here !/5. Classification and Regression/2. Regression process of a machine model. What is leaner regression.mp4 75.9 MB
~Get Your Files Here !/5. Classification and Regression/1. Classification process of machine model to explore and analyze the data.mp4 75.7 MB
~Get Your Files Here !/2. Introduction to Machine Learning/3. Machine learning vs Deep learning vs Artificial intelligence vs Data Science.mp4 74.0 MB
~Get Your Files Here !/4. Confusion Matrix, Under-fitting & Over-fitting/4. Under-fitting & Over-fitting of a Machine model. Understand it graphically.mp4 67.2 MB
~Get Your Files Here !/2. Introduction to Machine Learning/2. Understand machine learning concept by the examples we face in daily life.mp4 63.3 MB
~Get Your Files Here !/7. K-Nearest Neighbors Classifier (KNN)/2. How to KNN machine model works Understand it graphically.mp4 61.9 MB
~Get Your Files Here !/4. Confusion Matrix, Under-fitting & Over-fitting/1. Table of a confusion matrix and derive the predicted and actual values.mp4 58.9 MB
~Get Your Files Here !/7. K-Nearest Neighbors Classifier (KNN)/3. Concept of KNN machine model with a daily a life example. Check it graphically.mp4 55.7 MB
~Get Your Files Here !/7. K-Nearest Neighbors Classifier (KNN)/4. Choosing of an accurate of k value. Why k value is important in KNN model.mp4 51.8 MB
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18_Add Ctrl's In Head_3.mp4 151.3 MB
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~Get Your Files Here !/13. Implementation, Optimization and Training Of Segmentation Models/1. Implement Segmentation Models (UNet, PSPNet, DeepLab, PAN, and UNet++).mp4 208.6 MB
~Get Your Files Here !/23. Training, Evaluating and Visualizing Instance Segmentation on Custom Dataset/1. Train, Evaluate Instance Segmentation Model & Visualizing Results on Custom Data.mp4 187.5 MB
~Get Your Files Here !/18. Detectron2 for Ojbect Detection/1. Detectron2 for Ojbect Detection with PyTorch.mp4 173.4 MB
~Get Your Files Here !/10. Segmentation Datasets, Annotations, Data Augmentation & Data Loading/3. Data Loading with PyTorch Customized Dataset Class.mp4 167.4 MB
~Get Your Files Here !/19. Training, Evaluating and Visualizing Object Detection on Custom Dataset/3. Train, Evaluate Object Detection Models & Visualizing Results on Custom Dataset.mp4 162.4 MB
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~Get Your Files Here !/7. Transfer Learning for Image Classification/4. FineTuning Deep ResNet Model.mp4 73.2 MB
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Lecture 14 - Visualizing and Understanding-G1hGwHVykDU.mp4 208.9 MB
Lecture 11 - Training Neural Networks II-WUazOtlti0g.mp4 201.1 MB
Lecture 18 - Videos-A9D6NXBJdwU.mp4 200.5 MB
Lecture 20 - Generative Models II-igP03FXZqgo.mp4 196.4 MB
Lecture 15 - Object Detection-TB-fdISzpHQ.mp4 189.2 MB
Lecture 16 - Detection and Segmentation-9AyMR4IhSWQ.mp4 187.9 MB
Lecture 12 - Recurrent Networks-dUzLD91Sj-o.mp4 187.7 MB
Lecture 6 - Backpropagation-dB-u77Y5a6A.mp4 186.0 MB
Lecture 3 - Linear Classifiers-qcSEP17uKKY.mp4 180.1 MB
Lecture 8 - CNN Architectures-XaZIlVrIO-Q.mp4 174.3 MB
Lecture 17 - 3D Vision-S1_nCdLUQQ8.mp4 171.4 MB
Lecture 22 - Conclusion-s3Ky_Ls4YSY.mp4 170.3 MB
Lecture 19 - Generative Models I-Q3HU2vEhD5Y.mp4 168.7 MB
Lecture 2 - Image Classification-0nqvO3AM2Vw.mp4 168.2 MB
Lecture 21 - Reinforcement Learning-Qex3XzcFKP4.mp4 166.6 MB
Lecture 10 - Training Neural Networks I-lGbQlr1Ts7w.mp4 160.2 MB
Lecture 13 - Attention-YAgjfMR9R_M.mp4 160.0 MB
Lecture 9 - Hardware and Software-oXPX8GIOiU4.mp4 156.5 MB
Lecture 1 - Introduction to Deep Learning for Computer Vision-dJYGatp4SvA.mp4 152.7 MB
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