Udemy - Machine Learning A-Z Become Kaggle Master

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1. Python Fundamentals/1. Introduction to the course.mp498.41MB
1. Python Fundamentals/1. Introduction to the course.vtt16.72kB
1. Python Fundamentals/10. Functions.mp489.78MB
1. Python Fundamentals/10. Functions.vtt14.85kB
1. Python Fundamentals/11. String Part1.mp4111.16MB
1. Python Fundamentals/11. String Part1.vtt15.90kB
1. Python Fundamentals/12. String Part2.mp428.71MB
1. Python Fundamentals/12. String Part2.vtt3.53kB
1. Python Fundamentals/13. List Part1.mp410.53MB
1. Python Fundamentals/13. List Part1.vtt2.98kB
1. Python Fundamentals/14. List Part2.mp491.56MB
1. Python Fundamentals/14. List Part2.vtt13.49kB
1. Python Fundamentals/15. List Part3.mp477.13MB
1. Python Fundamentals/15. List Part3.vtt10.72kB
1. Python Fundamentals/16. List Part4.mp466.95MB
1. Python Fundamentals/16. List Part4.vtt10.68kB
1. Python Fundamentals/17. Tuples.mp470.60MB
1. Python Fundamentals/17. Tuples.vtt10.42kB
1. Python Fundamentals/18. Sets.mp460.98MB
1. Python Fundamentals/18. Sets.vtt7.99kB
1. Python Fundamentals/19. Dictionaries.mp464.59MB
1. Python Fundamentals/19. Dictionaries.vtt8.52kB
1. Python Fundamentals/2. Introduction to Kaggle.mp494.44MB
1. Python Fundamentals/2. Introduction to Kaggle.vtt11.41kB
1. Python Fundamentals/20. Comprehentions.mp473.97MB
1. Python Fundamentals/20. Comprehentions.vtt8.28kB
1. Python Fundamentals/3. Installation of Python and Anaconda.mp486.29MB
1. Python Fundamentals/3. Installation of Python and Anaconda.vtt11.38kB
1. Python Fundamentals/3.1 Python-code-udemy.zip.zip16.81kB
1. Python Fundamentals/3.2 Installing-Python.Teclov.pdf.pdf1.44MB
1. Python Fundamentals/4. Python Introduction.mp410.75MB
1. Python Fundamentals/4. Python Introduction.vtt3.63kB
1. Python Fundamentals/4.1 Python-code-udemy.zip.zip16.81kB
1. Python Fundamentals/5. Variables in Python.mp4115.83MB
1. Python Fundamentals/5. Variables in Python.vtt21.23kB
1. Python Fundamentals/6. Numeric Operations in Python.mp438.71MB
1. Python Fundamentals/6. Numeric Operations in Python.vtt7.31kB
1. Python Fundamentals/7. Logical Operations.mp418.16MB
1. Python Fundamentals/7. Logical Operations.vtt3.30kB
1. Python Fundamentals/8. If else Loop.mp467.12MB
1. Python Fundamentals/8. If else Loop.vtt10.27kB
1. Python Fundamentals/9. for while Loop.mp481.56MB
1. Python Fundamentals/9. for while Loop.vtt13.30kB
10. Multiple Linear Regression/1. Introduction.mp417.26MB
10. Multiple Linear Regression/1. Introduction.vtt3.72kB
10. Multiple Linear Regression/1.1 Multplr_LR_Code_for Udemy.zip.zip533.52kB
10. Multiple Linear Regression/10. Case Study Part5.mp447.95MB
10. Multiple Linear Regression/10. Case Study Part5.vtt6.25kB
10. Multiple Linear Regression/11. Case Study Part6 (RFE).mp467.26MB
10. Multiple Linear Regression/11. Case Study Part6 (RFE).vtt8.43kB
10. Multiple Linear Regression/2. Case Study part1.mp487.07MB
10. Multiple Linear Regression/2. Case Study part1.vtt8.71kB
10. Multiple Linear Regression/3. Case Study part2.mp4103.19MB
10. Multiple Linear Regression/3. Case Study part2.vtt12.48kB
10. Multiple Linear Regression/4. Case Study part3.mp472.01MB
10. Multiple Linear Regression/4. Case Study part3.vtt7.93kB
10. Multiple Linear Regression/5. Adjusted R Square.mp48.48MB
10. Multiple Linear Regression/5. Adjusted R Square.vtt0.86kB
10. Multiple Linear Regression/6. Case Study Part1.mp471.88MB
10. Multiple Linear Regression/6. Case Study Part1.vtt9.04kB
10. Multiple Linear Regression/7. Case Study Part2.mp476.44MB
10. Multiple Linear Regression/7. Case Study Part2.vtt12.61kB
10. Multiple Linear Regression/8. Case Study Part3.mp469.79MB
10. Multiple Linear Regression/8. Case Study Part3.vtt7.83kB
10. Multiple Linear Regression/9. Case Study Part4.mp4138.62MB
10. Multiple Linear Regression/9. Case Study Part4.vtt18.25kB
11. HotstarNetflix Real world Case Study for Multiple Linear Regression/1. Introduction to the Problem Statement.mp442.83MB
11. HotstarNetflix Real world Case Study for Multiple Linear Regression/1. Introduction to the Problem Statement.vtt6.39kB
11. HotstarNetflix Real world Case Study for Multiple Linear Regression/1.1 Hotstarcode-for-udemy.zip.zip260.71kB
11. HotstarNetflix Real world Case Study for Multiple Linear Regression/2. Playing With Data.mp485.31MB
11. HotstarNetflix Real world Case Study for Multiple Linear Regression/2. Playing With Data.vtt12.18kB
11. HotstarNetflix Real world Case Study for Multiple Linear Regression/3. Building Model Part1.mp457.74MB
11. HotstarNetflix Real world Case Study for Multiple Linear Regression/3. Building Model Part1.vtt5.98kB
11. HotstarNetflix Real world Case Study for Multiple Linear Regression/4. Building Model Part2.mp492.06MB
11. HotstarNetflix Real world Case Study for Multiple Linear Regression/4. Building Model Part2.vtt9.54kB
11. HotstarNetflix Real world Case Study for Multiple Linear Regression/5. Building Model Part3.mp450.87MB
11. HotstarNetflix Real world Case Study for Multiple Linear Regression/5. Building Model Part3.vtt4.76kB
11. HotstarNetflix Real world Case Study for Multiple Linear Regression/6. Verification of Model.mp441.41MB
11. HotstarNetflix Real world Case Study for Multiple Linear Regression/6. Verification of Model.vtt4.86kB
12. Gradient Descent/1. Pre-Req For Gradient Descent Part1.mp464.22MB
12. Gradient Descent/1. Pre-Req For Gradient Descent Part1.vtt18.00kB
12. Gradient Descent/1.1 Gradient+Descent+Updated.zip.zip165.02kB
12. Gradient Descent/2. Pre-Req For Gradient Descent Part2.mp434.49MB
12. Gradient Descent/2. Pre-Req For Gradient Descent Part2.vtt9.17kB
12. Gradient Descent/3. Cost Functions.mp413.79MB
12. Gradient Descent/3. Cost Functions.vtt2.90kB
12. Gradient Descent/4. Defining Cost Functions More Formally.mp438.29MB
12. Gradient Descent/4. Defining Cost Functions More Formally.vtt8.80kB
12. Gradient Descent/5. Gradient Descent.mp439.49MB
12. Gradient Descent/5. Gradient Descent.vtt12.81kB
12. Gradient Descent/6. Optimisation.mp422.73MB
12. Gradient Descent/6. Optimisation.vtt5.18kB
12. Gradient Descent/7. Closed Form Vs Gradient Descent.mp427.90MB
12. Gradient Descent/7. Closed Form Vs Gradient Descent.vtt5.91kB
12. Gradient Descent/8. Gradient Descent case study.mp475.14MB
12. Gradient Descent/8. Gradient Descent case study.vtt7.02kB
13. KNN/1. Introduction to Classification.mp456.74MB
13. KNN/1. Introduction to Classification.vtt15.90kB
13. KNN/1.1 KNN.zip.zip1.40MB
13. KNN/10. Case Study.mp474.14MB
13. KNN/10. Case Study.vtt11.06kB
13. KNN/11. Classification Case1.mp488.32MB
13. KNN/11. Classification Case1.vtt25.62kB
13. KNN/12. Classification Case2.mp454.77MB
13. KNN/12. Classification Case2.vtt17.34kB
13. KNN/13. Classification Case3.mp455.54MB
13. KNN/13. Classification Case3.vtt15.58kB
13. KNN/14. Classification Case4.mp443.09MB
13. KNN/14. Classification Case4.vtt14.12kB
13. KNN/2. Defining Classification Mathematically.mp441.93MB
13. KNN/2. Defining Classification Mathematically.vtt9.24kB
13. KNN/3. Introduction to KNN.mp449.41MB
13. KNN/3. Introduction to KNN.vtt14.02kB
13. KNN/4. Accuracy of KNN.mp459.93MB
13. KNN/4. Accuracy of KNN.vtt15.21kB
13. KNN/5. Effectiveness of KNN.mp450.57MB
13. KNN/5. Effectiveness of KNN.vtt16.24kB
13. KNN/6. Distance Metrics.mp450.22MB
13. KNN/6. Distance Metrics.vtt15.00kB
13. KNN/7. Distance Metrics Part2.mp430.23MB
13. KNN/7. Distance Metrics Part2.vtt9.48kB
13. KNN/8. Finding k.mp434.94MB
13. KNN/8. Finding k.vtt11.77kB
13. KNN/9. KNN on Regression.mp49.73MB
13. KNN/9. KNN on Regression.vtt3.00kB
14. Model Performance Metrics/1. Performance Metrics Part1.mp4119.36MB
14. Model Performance Metrics/1. Performance Metrics Part1.vtt27.79kB
14. Model Performance Metrics/2. Performance Metrics Part2.mp494.88MB
14. Model Performance Metrics/2. Performance Metrics Part2.vtt19.61kB
14. Model Performance Metrics/3. Performance Metrics Part3.mp425.19MB
14. Model Performance Metrics/3. Performance Metrics Part3.vtt6.39kB
15. Model Selection Part1/1. Model Creation Case1.mp454.62MB
15. Model Selection Part1/1. Model Creation Case1.vtt12.72kB
15. Model Selection Part1/1.1 CrossValidation_Linear Regression.zip.zip350.43kB
15. Model Selection Part1/2. Model Creation Case2.mp436.35MB
15. Model Selection Part1/2. Model Creation Case2.vtt8.99kB
15. Model Selection Part1/3. Gridsearch Case study Part1.mp4130.28MB
15. Model Selection Part1/3. Gridsearch Case study Part1.vtt13.80kB
15. Model Selection Part1/4. Gridsearch Case study Part2.mp4187.57MB
15. Model Selection Part1/4. Gridsearch Case study Part2.vtt18.89kB
16. Naive Bayes/1. Introduction to Naive Bayes.mp476.94MB
16. Naive Bayes/1. Introduction to Naive Bayes.vtt18.22kB
16. Naive Bayes/1.1 NaiveBayes.zip.zip272.42kB
16. Naive Bayes/10. Case Study 2 Part1.mp478.20MB
16. Naive Bayes/10. Case Study 2 Part1.vtt9.12kB
16. Naive Bayes/11. Case Study 2 Part2.mp426.58MB
16. Naive Bayes/11. Case Study 2 Part2.vtt3.04kB
16. Naive Bayes/2. Bayes Theorem.mp466.11MB
16. Naive Bayes/2. Bayes Theorem.vtt13.05kB
16. Naive Bayes/3. Practical Example from NB with One Column.mp484.50MB
16. Naive Bayes/3. Practical Example from NB with One Column.vtt10.93kB
16. Naive Bayes/4. Practical Example from NB with Multiple Columns.mp462.74MB
16. Naive Bayes/4. Practical Example from NB with Multiple Columns.vtt13.47kB
16. Naive Bayes/5. Naive Bayes On Text Data Part1.mp457.40MB
16. Naive Bayes/5. Naive Bayes On Text Data Part1.vtt10.23kB
16. Naive Bayes/6. Naive Bayes On Text Data Part2.mp448.30MB
16. Naive Bayes/6. Naive Bayes On Text Data Part2.vtt6.74kB
16. Naive Bayes/7. Laplace Smoothing.mp457.95MB
16. Naive Bayes/7. Laplace Smoothing.vtt5.06kB
16. Naive Bayes/8. Bernoulli Naive Bayes.mp428.42MB
16. Naive Bayes/8. Bernoulli Naive Bayes.vtt2.09kB
16. Naive Bayes/9. Case Study 1.mp4100.10MB
16. Naive Bayes/9. Case Study 1.vtt11.07kB
17. Logistic Regression/1. Introduction.mp427.89MB
17. Logistic Regression/1. Introduction.vtt8.38kB
17. Logistic Regression/1.1 LogisticReg.zip.zip1.01MB
17. Logistic Regression/2. Sigmoid Function.mp446.46MB
17. Logistic Regression/2. Sigmoid Function.vtt11.91kB
17. Logistic Regression/3. Log Odds.mp443.86MB
17. Logistic Regression/3. Log Odds.vtt11.17kB
17. Logistic Regression/4. Case Study.mp4207.83MB
17. Logistic Regression/4. Case Study.vtt20.90kB
18. Support Vector Machine (SVM)/1. Introduction.mp461.56MB
18. Support Vector Machine (SVM)/1. Introduction.vtt14.05kB
18. Support Vector Machine (SVM)/1.1 SVM.zip.zip16.16MB
18. Support Vector Machine (SVM)/10. Kernel Part2.mp474.59MB
18. Support Vector Machine (SVM)/10. Kernel Part2.vtt12.98kB
18. Support Vector Machine (SVM)/11. Case Study 2.mp494.38MB
18. Support Vector Machine (SVM)/11. Case Study 2.vtt8.56kB
18. Support Vector Machine (SVM)/12. Case Study 3 Part1.mp458.73MB
18. Support Vector Machine (SVM)/12. Case Study 3 Part1.vtt10.16kB
18. Support Vector Machine (SVM)/13. Case Study 3 Part2.mp464.26MB
18. Support Vector Machine (SVM)/13. Case Study 3 Part2.vtt6.39kB
18. Support Vector Machine (SVM)/14. Case Study 4.mp4172.40MB
18. Support Vector Machine (SVM)/14. Case Study 4.vtt20.86kB
18. Support Vector Machine (SVM)/2. Hyperplane Part1.mp428.38MB
18. Support Vector Machine (SVM)/2. Hyperplane Part1.vtt6.25kB
18. Support Vector Machine (SVM)/3. Hyperplane Part2.mp468.49MB
18. Support Vector Machine (SVM)/3. Hyperplane Part2.vtt17.17kB
18. Support Vector Machine (SVM)/4. Maths Behind SVM.mp425.21MB
18. Support Vector Machine (SVM)/4. Maths Behind SVM.vtt8.34kB
18. Support Vector Machine (SVM)/5. Support Vectors.mp411.58MB
18. Support Vector Machine (SVM)/5. Support Vectors.vtt4.05kB
18. Support Vector Machine (SVM)/6. Slack Variable.mp434.89MB
18. Support Vector Machine (SVM)/6. Slack Variable.vtt10.47kB
18. Support Vector Machine (SVM)/7. SVM Case Study Part1.mp477.75MB
18. Support Vector Machine (SVM)/7. SVM Case Study Part1.vtt6.64kB
18. Support Vector Machine (SVM)/8. SVM Case Study Part2.mp469.37MB
18. Support Vector Machine (SVM)/8. SVM Case Study Part2.vtt8.61kB
18. Support Vector Machine (SVM)/9. Kernel Part1.mp451.63MB
18. Support Vector Machine (SVM)/9. Kernel Part1.vtt9.58kB
19. Decision Tree/1. Introduction.mp431.22MB
19. Decision Tree/1. Introduction.vtt9.18kB
19. Decision Tree/1.1 DT_forudemy.zip.zip4.22MB
19. Decision Tree/10. DT Case Study Part2.mp4100.36MB
19. Decision Tree/10. DT Case Study Part2.vtt11.17kB
19. Decision Tree/2. Example of DT.mp442.56MB
19. Decision Tree/2. Example of DT.vtt9.39kB
19. Decision Tree/3. Homogenity.mp421.61MB
19. Decision Tree/3. Homogenity.vtt5.98kB
19. Decision Tree/4. Gini Index.mp446.33MB
19. Decision Tree/4. Gini Index.vtt9.09kB
19. Decision Tree/5. Information Gain Part1.mp430.71MB
19. Decision Tree/5. Information Gain Part1.vtt6.84kB
19. Decision Tree/6. Information Gain Part2.mp428.70MB
19. Decision Tree/6. Information Gain Part2.vtt5.79kB
19. Decision Tree/7. Advantages and Disadvantages of DT.mp416.20MB
19. Decision Tree/7. Advantages and Disadvantages of DT.vtt4.54kB
19. Decision Tree/8. Preventing Overfitting Issues in DT.mp442.24MB
19. Decision Tree/8. Preventing Overfitting Issues in DT.vtt12.06kB
19. Decision Tree/9. DT Case Study Part1.mp4131.55MB
19. Decision Tree/9. DT Case Study Part1.vtt13.23kB
2. Numpy/1. Introduction.mp425.95MB
2. Numpy/1. Introduction.vtt6.42kB
2. Numpy/1.1 Teclov-numpy.ipynb.zip.zip5.28kB
2. Numpy/2. Numpy Operations Part1.mp4135.00MB
2. Numpy/2. Numpy Operations Part1.vtt24.41kB
2. Numpy/3. Numpy Operations Part2.mp4178.23MB
2. Numpy/3. Numpy Operations Part2.vtt30.51kB
20. Ensembling/1. Introduction to Ensembles.mp441.19MB
20. Ensembling/1. Introduction to Ensembles.vtt11.35kB
20. Ensembling/1.1 Boosting.zip.zip1.32MB
20. Ensembling/1.2 RF_forudemy.zip.zip1.10MB
20. Ensembling/10. Adaboost Part2.mp440.33MB
20. Ensembling/10. Adaboost Part2.vtt8.12kB
20. Ensembling/11. Adaboost Case Study.mp456.26MB
20. Ensembling/11. Adaboost Case Study.vtt6.15kB
20. Ensembling/12. XGBoost.mp424.23MB
20. Ensembling/12. XGBoost.vtt4.86kB
20. Ensembling/13. Boosting Part1.mp414.35MB
20. Ensembling/13. Boosting Part1.vtt3.79kB
20. Ensembling/14. Boosting Part2.mp437.24MB
20. Ensembling/14. Boosting Part2.vtt8.01kB
20. Ensembling/15. XGboost Algorithm.mp440.65MB
20. Ensembling/15. XGboost Algorithm.vtt9.01kB
20. Ensembling/16. Case Study Part1.mp4148.42MB
20. Ensembling/16. Case Study Part1.vtt12.06kB
20. Ensembling/17. Case Study Part2.mp4143.34MB
20. Ensembling/17. Case Study Part2.vtt13.70kB
20. Ensembling/18. Case Study Part3.mp479.10MB
20. Ensembling/18. Case Study Part3.vtt7.04kB
20. Ensembling/2. Bagging.mp474.67MB
20. Ensembling/2. Bagging.vtt15.81kB
20. Ensembling/3. Advantages.mp415.59MB
20. Ensembling/3. Advantages.vtt5.19kB
20. Ensembling/4. Runtime.mp417.18MB
20. Ensembling/4. Runtime.vtt4.77kB
20. Ensembling/5. Case study.mp476.64MB
20. Ensembling/5. Case study.vtt7.06kB
20. Ensembling/6. Introduction to Boosting.mp434.65MB
20. Ensembling/6. Introduction to Boosting.vtt6.63kB
20. Ensembling/7. Weak Learners.mp418.77MB
20. Ensembling/7. Weak Learners.vtt3.19kB
20. Ensembling/8. Shallow Decision Tree.mp415.68MB
20. Ensembling/8. Shallow Decision Tree.vtt2.79kB
20. Ensembling/9. Adaboost Part1.mp443.55MB
20. Ensembling/9. Adaboost Part1.vtt8.45kB
21. Model Selection Part2/1. Model Selection Part1.mp4109.37MB
21. Model Selection Part2/1. Model Selection Part1.vtt23.76kB
21. Model Selection Part2/2. Model Selection Part2.mp443.33MB
21. Model Selection Part2/2. Model Selection Part2.vtt14.89kB
21. Model Selection Part2/3. Model Selection Part3.mp437.39MB
22. Unsupervised Learning/1. Introduction to Clustering.mp462.00MB
22. Unsupervised Learning/1. Introduction to Clustering.vtt12.99kB
22. Unsupervised Learning/1.1 Unsupervised.zip.zip7.74MB
22. Unsupervised Learning/10. Case Study Part2.mp464.31MB
22. Unsupervised Learning/10. Case Study Part2.vtt9.26kB
22. Unsupervised Learning/11. More on Segmentation.mp418.94MB
22. Unsupervised Learning/11. More on Segmentation.vtt5.63kB
22. Unsupervised Learning/12. Hierarchial Clustering.mp439.87MB
22. Unsupervised Learning/12. Hierarchial Clustering.vtt9.25kB
22. Unsupervised Learning/13. Case Study.mp436.07MB
22. Unsupervised Learning/13. Case Study.vtt6.69kB
22. Unsupervised Learning/2. Segmentation.mp430.04MB
22. Unsupervised Learning/2. Segmentation.vtt8.91kB
22. Unsupervised Learning/3. Kmeans.mp460.51MB
22. Unsupervised Learning/3. Kmeans.vtt10.37kB
22. Unsupervised Learning/4. Maths Behind Kmeans.mp456.37MB
22. Unsupervised Learning/4. Maths Behind Kmeans.vtt13.50kB
22. Unsupervised Learning/5. More Maths.mp49.89MB
22. Unsupervised Learning/5. More Maths.vtt2.98kB
22. Unsupervised Learning/6. Kmeans plus.mp454.30MB
22. Unsupervised Learning/6. Kmeans plus.vtt11.70kB
22. Unsupervised Learning/7. Value of K.mp437.56MB
22. Unsupervised Learning/7. Value of K.vtt7.80kB
22. Unsupervised Learning/8. Hopkins test.mp412.87MB
22. Unsupervised Learning/8. Hopkins test.vtt3.09kB
22. Unsupervised Learning/9. Case Study Part1.mp4100.47MB
22. Unsupervised Learning/9. Case Study Part1.vtt13.50kB
23. Dimension Reduction/1. Introduction.mp4164.29MB
23. Dimension Reduction/1. Introduction.vtt32.94kB
23. Dimension Reduction/1.1 PCA code for udemy.zip.zip9.50MB
23. Dimension Reduction/2. PCA.mp4103.17MB
23. Dimension Reduction/2. PCA.vtt27.08kB
23. Dimension Reduction/3. Maths Behind PCA.mp4101.52MB
23. Dimension Reduction/3. Maths Behind PCA.vtt26.13kB
23. Dimension Reduction/4. Case Study Part1.mp447.68MB
23. Dimension Reduction/4. Case Study Part1.vtt6.22kB
23. Dimension Reduction/5. Case Study Part2.mp4129.03MB
23. Dimension Reduction/5. Case Study Part2.vtt19.43kB
24. Advanced Machine Learning Algorithms/1. Introduction.mp432.44MB
24. Advanced Machine Learning Algorithms/1. Introduction.vtt7.35kB
24. Advanced Machine Learning Algorithms/1.1 AdvanceReg.zip.zip1.17MB
24. Advanced Machine Learning Algorithms/10. Adjusted R Square.mp421.11MB
24. Advanced Machine Learning Algorithms/10. Adjusted R Square.vtt4.18kB
24. Advanced Machine Learning Algorithms/2. Example Part1.mp428.81MB
24. Advanced Machine Learning Algorithms/2. Example Part1.vtt6.18kB
24. Advanced Machine Learning Algorithms/3. Example Part2.mp447.31MB
24. Advanced Machine Learning Algorithms/3. Example Part2.vtt11.00kB
24. Advanced Machine Learning Algorithms/4. Optimal Solution.mp468.40MB
24. Advanced Machine Learning Algorithms/4. Optimal Solution.vtt17.11kB
24. Advanced Machine Learning Algorithms/5. Case study.mp441.91MB
24. Advanced Machine Learning Algorithms/5. Case study.vtt4.31kB
24. Advanced Machine Learning Algorithms/6. Regularization.mp450.96MB
24. Advanced Machine Learning Algorithms/6. Regularization.vtt10.56kB
24. Advanced Machine Learning Algorithms/7. Ridge and Lasso.mp441.89MB
24. Advanced Machine Learning Algorithms/7. Ridge and Lasso.vtt7.88kB
24. Advanced Machine Learning Algorithms/8. Case Study.mp4111.38MB
24. Advanced Machine Learning Algorithms/8. Case Study.vtt10.94kB
24. Advanced Machine Learning Algorithms/9. Model Selection.mp432.82MB
24. Advanced Machine Learning Algorithms/9. Model Selection.vtt6.68kB
25. Deep Learning/1. Expectations.mp49.82MB
25. Deep Learning/1. Expectations.vtt2.86kB
25. Deep Learning/2. Introduction.mp451.13MB
25. Deep Learning/2. Introduction.vtt10.83kB
25. Deep Learning/3. History.mp464.87MB
25. Deep Learning/3. History.vtt18.40kB
25. Deep Learning/4. Perceptron.mp431.23MB
25. Deep Learning/4. Perceptron.vtt8.44kB
25. Deep Learning/5. Multi Layered Perceptron.mp466.93MB
25. Deep Learning/5. Multi Layered Perceptron.vtt14.84kB
25. Deep Learning/6. Neural Network Playground.mp4108.73MB
25. Deep Learning/6. Neural Network Playground.vtt13.92kB
26. Project Kaggle/1. Introduction to the Problem Statement.mp497.89MB
26. Project Kaggle/1. Introduction to the Problem Statement.vtt9.87kB
26. Project Kaggle/1.1 training.zip.zip62.91MB
26. Project Kaggle/1.2 Teclov Project - Medical treatment.ipynb.zip.zip1.35MB
26. Project Kaggle/10. Response encoding and one hot encoder.mp457.34MB
26. Project Kaggle/10. Response encoding and one hot encoder.vtt6.73kB
26. Project Kaggle/11. Laplace Smoothing and Calibrated classifier.mp450.59MB
26. Project Kaggle/11. Laplace Smoothing and Calibrated classifier.vtt14.76kB
26. Project Kaggle/12. Significance of first categorical column.mp475.23MB
26. Project Kaggle/12. Significance of first categorical column.vtt9.12kB
26. Project Kaggle/13. Second Categorical column.mp447.92MB
26. Project Kaggle/13. Second Categorical column.vtt5.40kB
26. Project Kaggle/14. Third Categorical column.mp469.96MB
26. Project Kaggle/14. Third Categorical column.vtt8.78kB
26. Project Kaggle/15. Data pre-processing before building machine learning model.mp453.04MB
26. Project Kaggle/15. Data pre-processing before building machine learning model.vtt5.78kB
26. Project Kaggle/16. Building Machine Learning model part1.mp4130.04MB
26. Project Kaggle/16. Building Machine Learning model part1.vtt17.72kB
26. Project Kaggle/17. Building Machine Learning model part2.mp4141.75MB
26. Project Kaggle/17. Building Machine Learning model part2.vtt15.67kB
26. Project Kaggle/18. Building Machine Learning model part3.mp440.28MB
26. Project Kaggle/18. Building Machine Learning model part3.vtt4.26kB
26. Project Kaggle/19. Building Machine Learning model part4.mp434.68MB
26. Project Kaggle/19. Building Machine Learning model part4.vtt4.01kB
26. Project Kaggle/2. Playing With The Data.mp4143.71MB
26. Project Kaggle/2. Playing With The Data.vtt18.33kB
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26. Project Kaggle/3. Translating the Problem In Machine Learning World.mp4118.51MB
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26. Project Kaggle/4. Dealing with Text Data.mp4102.82MB
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26. Project Kaggle/5. Train, Test And Cross Validation Split.mp4121.85MB
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26. Project Kaggle/6. Understanding Evaluation Matrix Log Loss.mp489.66MB
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26. Project Kaggle/7. Building A Worst Model.mp471.81MB
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26. Project Kaggle/8. Evaluating Worst ML Model.mp461.73MB
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26. Project Kaggle/9. First Categorical column analysis.mp474.58MB
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3. Pandas/1. Introduction.mp441.00MB
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3. Pandas/10. groupby.mp449.20MB
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3. Pandas/12. Pivot Table.mp429.05MB
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3. Pandas/8. Reading CSV.mp444.53MB
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3. Pandas/9. Merging Part1.mp431.47MB
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4. Some Fun With Maths/1. Linear Algebra Vectors.mp4170.30MB
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4. Some Fun With Maths/2. Linear Algebra Matrix Part1.mp499.89MB
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4. Some Fun With Maths/3. Linear Algebra Matrix Part2.mp481.78MB
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4. Some Fun With Maths/5. Linear Algebra 2D to nD Part2.mp427.03MB
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5. Inferential Statistics/1. Inferential Statistics.mp410.81MB
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5. Inferential Statistics/10. Normal Distribution.mp419.95MB
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5. Inferential Statistics/11. z Score.mp424.95MB
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5. Inferential Statistics/12. Sampling.mp440.61MB
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5. Inferential Statistics/13. Sampling Distribution.mp426.75MB
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5. Inferential Statistics/14. Central Limit Theorem.mp413.74MB
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5. Inferential Statistics/15. Confidence Interval Part1.mp436.22MB
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5. Inferential Statistics/9. PDF.mp422.02MB
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6. Hypothesis Testing/1. Introduction.mp432.60MB
6. Hypothesis Testing/1. Introduction.vtt9.42kB
6. Hypothesis Testing/1.1 z-table.pdf.pdf60.39kB
6. Hypothesis Testing/1.2 t-table.pdf.pdf150.84kB
6. Hypothesis Testing/10. Types of Error.mp416.04MB
6. Hypothesis Testing/10. Types of Error.vtt3.49kB
6. Hypothesis Testing/11. t- distribution Part1.mp422.35MB
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6. Hypothesis Testing/2. NULL And Alternate Hypothesis.mp430.19MB
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6. Hypothesis Testing/5. Critical Value Method.mp425.91MB
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6. Hypothesis Testing/6. z Table.mp461.48MB
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7. Data Visualisation/1.1 Datavisual.zip.zip1.26MB
7. Data Visualisation/2. Seaborn.mp4193.72MB
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7. Data Visualisation/3. Case Study.mp4118.70MB
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7. Data Visualisation/4. Seaborn On Time Series Data.mp456.68MB
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8. Exploratory Data Analysis/1. Introduction.mp43.98MB
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8. Exploratory Data Analysis/10. Univariate Analysis Part1.mp486.80MB
8. Exploratory Data Analysis/10. Univariate Analysis Part1.vtt26.41kB
8. Exploratory Data Analysis/11. Univariate Analysis Part2.mp463.81MB
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8. Exploratory Data Analysis/12. Segmented Analysis.mp425.66MB
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8. Exploratory Data Analysis/13. Bivariate Analysis.mp463.54MB
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8. Exploratory Data Analysis/14. Derived Columns.mp443.93MB
8. Exploratory Data Analysis/14. Derived Columns.vtt14.75kB
8. Exploratory Data Analysis/2. Data Sourcing and Cleaning part1.mp416.31MB
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8. Exploratory Data Analysis/5. Data Sourcing and Cleaning part4.mp410.88MB
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8. Exploratory Data Analysis/6. Data Sourcing and Cleaning part5.mp413.02MB
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8. Exploratory Data Analysis/8. Data Cleaning part1.mp479.94MB
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8. Exploratory Data Analysis/9. Data Cleaning part2.mp431.14MB
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9. Simple Linear Regression/1. Introduction to Machine Learning.mp411.70MB
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9. Simple Linear Regression/1.1 code-LR-Teclov.zip.zip78.68kB
9. Simple Linear Regression/10. Residual Square Error (RSE).mp44.77MB
9. Simple Linear Regression/10. Residual Square Error (RSE).vtt1.05kB
9. Simple Linear Regression/2. Types of Machine Learning.mp437.09MB
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9. Simple Linear Regression/4. How LR Works.vtt10.17kB
9. Simple Linear Regression/5. Some Fun With Maths Behind LR.mp455.31MB
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9. Simple Linear Regression/6. R Square.mp455.02MB
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9. Simple Linear Regression/7. LR Case Study Part1.mp4144.18MB
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[CourseClub.NET].url0.12kB
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[FreeCourseSite.com].url0.13kB
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