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DesireCourse Net Udemy Machine Learning Data Science and Deep Learning with Python

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[DesireCourse.Net] Udemy - Machine Learning, Data Science and Deep Learning with Python

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Total Size

8.3 GB

Total Files

224

Hash

368E6AF103BCD0D165EA82156B8B289AAC962D2E

/1. Getting Started/

1. Introduction.mp4

62.5 MB

1. Introduction.srt

4.9 KB

10. [Activity] Python Basics, Part 4 [Optional].mp4

22.1 MB

10. [Activity] Python Basics, Part 4 [Optional].srt

6.1 KB

11. Introducing the Pandas Library [Optional].mp4

129.1 MB

11. Introducing the Pandas Library [Optional].srt

18.5 KB

2. Udemy 101 Getting the Most From This Course.mp4

20.7 MB

2. Udemy 101 Getting the Most From This Course.srt

4.1 KB

3. Installation Getting Started.html

0.3 KB

4. [Activity] WINDOWS Installing and Using Anaconda & Course Materials.mp4

107.8 MB

4. [Activity] WINDOWS Installing and Using Anaconda & Course Materials.srt

19.3 KB

5. [Activity] MAC Installing and Using Anaconda & Course Materials.mp4

101.2 MB

5. [Activity] MAC Installing and Using Anaconda & Course Materials.srt

14.8 KB

6. [Activity] LINUX Installing and Using Anaconda & Course Materials.mp4

84.1 MB

6. [Activity] LINUX Installing and Using Anaconda & Course Materials.srt

15.0 KB

7. Python Basics, Part 1 [Optional].mp4

34.6 MB

7. Python Basics, Part 1 [Optional].srt

7.9 KB

8. [Activity] Python Basics, Part 2 [Optional].mp4

21.6 MB

8. [Activity] Python Basics, Part 2 [Optional].srt

7.8 KB

9. [Activity] Python Basics, Part 3 [Optional].mp4

10.6 MB

9. [Activity] Python Basics, Part 3 [Optional].srt

4.3 KB

/10. Deep Learning and Neural Networks/

1. Deep Learning Pre-Requisites.mp4

77.8 MB

1. Deep Learning Pre-Requisites.srt

22.0 KB

10. [Activity] Using Keras to Predict Political Affiliations.mp4

92.5 MB

10. [Activity] Using Keras to Predict Political Affiliations.srt

21.6 KB

11. Convolutional Neural Networks (CNN's).mp4

97.6 MB

11. Convolutional Neural Networks (CNN's).srt

20.3 KB

12. [Activity] Using CNN's for handwriting recognition.mp4

72.9 MB

12. [Activity] Using CNN's for handwriting recognition.srt

14.1 KB

13. Recurrent Neural Networks (RNN's).mp4

72.5 MB

13. Recurrent Neural Networks (RNN's).srt

18.9 KB

14. [Activity] Using a RNN for sentiment analysis.mp4

85.3 MB

14. [Activity] Using a RNN for sentiment analysis.srt

17.2 KB

15. [Activity] Transfer Learning.mp4

120.9 MB

15. [Activity] Transfer Learning.srt

22.0 KB

16. Tuning Neural Networks Learning Rate and Batch Size Hyperparameters.mp4

19.3 MB

16. Tuning Neural Networks Learning Rate and Batch Size Hyperparameters.srt

8.5 KB

17. Deep Learning Regularization with Dropout and Early Stopping.mp4

35.3 MB

17. Deep Learning Regularization with Dropout and Early Stopping.srt

12.3 KB

18. The Ethics of Deep Learning.mp4

134.5 MB

18. The Ethics of Deep Learning.srt

20.3 KB

19. Learning More about Deep Learning.mp4

40.5 MB

19. Learning More about Deep Learning.srt

3.2 KB

2. The History of Artificial Neural Networks.mp4

83.9 MB

2. The History of Artificial Neural Networks.srt

19.5 KB

3. [Activity] Deep Learning in the Tensorflow Playground.mp4

148.5 MB

3. [Activity] Deep Learning in the Tensorflow Playground.srt

20.1 KB

4. Deep Learning Details.mp4

67.3 MB

4. Deep Learning Details.srt

17.2 KB

5. Introducing Tensorflow.mp4

67.3 MB

5. Introducing Tensorflow.srt

20.2 KB

6. Important note about Tensorflow 2.html

0.6 KB

7. [Activity] Using Tensorflow, Part 1.mp4

124.0 MB

7. [Activity] Using Tensorflow, Part 1.srt

23.6 KB

8. [Activity] Using Tensorflow, Part 2.mp4

109.6 MB

8. [Activity] Using Tensorflow, Part 2.srt

21.7 KB

9. [Activity] Introducing Keras.mp4

96.5 MB

9. [Activity] Introducing Keras.srt

24.3 KB

/11. Final Project/

1. Your final project assignment.mp4

54.1 MB

1. Your final project assignment.srt

11.8 KB

2. Final project review.mp4

103.3 MB

2. Final project review.srt

25.1 KB

/12. You made it!/

1. More to Explore.mp4

67.2 MB

1. More to Explore.srt

7.4 KB

2. Don't Forget to Leave a Rating!.html

0.6 KB

3. Bonus Lecture More courses to explore!.html

7.5 KB

/2. Statistics and Probability Refresher, and Python Practice/

1. Types of Data.mp4

81.0 MB

1. Types of Data.srt

16.6 KB

10. [Activity] Covariance and Correlation.mp4

122.4 MB

10. [Activity] Covariance and Correlation.srt

26.5 KB

11. [Exercise] Conditional Probability.mp4

131.2 MB

11. [Exercise] Conditional Probability.srt

29.1 KB

12. Exercise Solution Conditional Probability of Purchase by Age.mp4

23.1 MB

12. Exercise Solution Conditional Probability of Purchase by Age.srt

4.1 KB

13. Bayes' Theorem.mp4

61.8 MB

13. Bayes' Theorem.srt

11.8 KB

2. Mean, Median, Mode.mp4

58.9 MB

2. Mean, Median, Mode.srt

13.3 KB

3. [Activity] Using mean, median, and mode in Python.mp4

64.9 MB

3. [Activity] Using mean, median, and mode in Python.srt

15.4 KB

4. [Activity] Variation and Standard Deviation.mp4

116.2 MB

4. [Activity] Variation and Standard Deviation.srt

26.5 KB

5. Probability Density Function; Probability Mass Function.mp4

31.5 MB

5. Probability Density Function; Probability Mass Function.srt

7.8 KB

6. Common Data Distributions.mp4

79.0 MB

6. Common Data Distributions.srt

16.5 KB

7. [Activity] Percentiles and Moments.mp4

119.6 MB

7. [Activity] Percentiles and Moments.srt

29.0 KB

8. [Activity] A Crash Course in matplotlib.mp4

135.6 MB

8. [Activity] A Crash Course in matplotlib.srt

29.3 KB

9. [Activity] Advanced Visualization with Seaborn.mp4

155.0 MB

9. [Activity] Advanced Visualization with Seaborn.srt

30.7 KB

/3. Predictive Models/

1. [Activity] Linear Regression.mp4

105.3 MB

1. [Activity] Linear Regression.srt

26.3 KB

2. [Activity] Polynomial Regression.mp4

70.0 MB

2. [Activity] Polynomial Regression.srt

18.0 KB

3. [Activity] Multiple Regression, and Predicting Car Prices.mp4

77.4 MB

3. [Activity] Multiple Regression, and Predicting Car Prices.srt

21.6 KB

4. Multi-Level Models.mp4

49.8 MB

4. Multi-Level Models.srt

10.9 KB

/4. Machine Learning with Python/

1. Supervised vs. Unsupervised Learning, and TrainTest.mp4

103.4 MB

1. Supervised vs. Unsupervised Learning, and TrainTest.srt

21.4 KB

10. [Activity] LINUX Installing Graphviz.mp4

7.4 MB

10. [Activity] LINUX Installing Graphviz.srt

1.1 KB

11. Decision Trees Concepts.mp4

90.7 MB

11. Decision Trees Concepts.srt

21.6 KB

12. [Activity] Decision Trees Predicting Hiring Decisions.mp4

100.6 MB

12. [Activity] Decision Trees Predicting Hiring Decisions.srt

23.0 KB

13. Ensemble Learning.mp4

68.4 MB

13. Ensemble Learning.srt

14.9 KB

14. [Activity] XGBoost.mp4

107.0 MB

14. [Activity] XGBoost.srt

29.4 KB

15. Support Vector Machines (SVM) Overview.mp4

46.9 MB

15. Support Vector Machines (SVM) Overview.srt

10.1 KB

16. [Activity] Using SVM to cluster people using scikit-learn.mp4

49.0 MB

16. [Activity] Using SVM to cluster people using scikit-learn.srt

17.0 KB

2. [Activity] Using TrainTest to Prevent Overfitting a Polynomial Regression.mp4

61.0 MB

2. [Activity] Using TrainTest to Prevent Overfitting a Polynomial Regression.srt

13.4 KB

3. Bayesian Methods Concepts.mp4

42.7 MB

3. Bayesian Methods Concepts.srt

9.0 KB

4. [Activity] Implementing a Spam Classifier with Naive Bayes.mp4

93.4 MB

4. [Activity] Implementing a Spam Classifier with Naive Bayes.srt

17.8 KB

5. K-Means Clustering.mp4

75.4 MB

5. K-Means Clustering.srt

17.6 KB

6. [Activity] Clustering people based on income and age.mp4

60.1 MB

6. [Activity] Clustering people based on income and age.srt

11.8 KB

7. Measuring Entropy.mp4

36.7 MB

7. Measuring Entropy.srt

7.1 KB

8. [Activity] WINDOWS Installing Graphviz.mp4

2.2 MB

8. [Activity] WINDOWS Installing Graphviz.srt

0.7 KB

9. [Activity] MAC Installing Graphviz.mp4

15.5 MB

9. [Activity] MAC Installing Graphviz.srt

1.3 KB

/5. Recommender Systems/

1. User-Based Collaborative Filtering.mp4

90.6 MB

1. User-Based Collaborative Filtering.srt

19.8 KB

2. Item-Based Collaborative Filtering.mp4

78.6 MB

2. Item-Based Collaborative Filtering.srt

20.5 KB

3. [Activity] Finding Movie Similarities.mp4

113.1 MB

3. [Activity] Finding Movie Similarities.srt

20.6 KB

4. [Activity] Improving the Results of Movie Similarities.mp4

99.5 MB

4. [Activity] Improving the Results of Movie Similarities.srt

17.2 KB

5. [Activity] Making Movie Recommendations to People.mp4

139.0 MB

5. [Activity] Making Movie Recommendations to People.srt

23.2 KB

6. [Exercise] Improve the recommender's results.mp4

88.3 MB

6. [Exercise] Improve the recommender's results.srt

13.5 KB

/6. More Data Mining and Machine Learning Techniques/

1. K-Nearest-Neighbors Concepts.mp4

42.2 MB

1. K-Nearest-Neighbors Concepts.srt

9.2 KB

2. [Activity] Using KNN to predict a rating for a movie.mp4

149.0 MB

2. [Activity] Using KNN to predict a rating for a movie.srt

29.2 KB

3. Dimensionality Reduction; Principal Component Analysis.mp4

71.0 MB

3. Dimensionality Reduction; Principal Component Analysis.srt

12.6 KB

4. [Activity] PCA Example with the Iris data set.mp4

115.1 MB

4. [Activity] PCA Example with the Iris data set.srt

21.7 KB

5. Data Warehousing Overview ETL and ELT.mp4

108.4 MB

5. Data Warehousing Overview ETL and ELT.srt

20.2 KB

6. Reinforcement Learning.mp4

138.7 MB

6. Reinforcement Learning.srt

29.2 KB

6.1 Pac-Man Example.html

0.1 KB

6.2 Cat and Mouse Example.html

0.1 KB

6.3 Python Markov Decision Process Toolbox.html

0.1 KB

7. [Activity] Reinforcement Learning & Q-Learning with Gym.mp4

81.7 MB

7. [Activity] Reinforcement Learning & Q-Learning with Gym.srt

23.0 KB

8. Understanding a Confusion Matrix.mp4

15.5 MB

8. Understanding a Confusion Matrix.srt

9.9 KB

9. Measuring Classifiers (Precision, Recall, F1, ROC, AUC).mp4

27.0 MB

9. Measuring Classifiers (Precision, Recall, F1, ROC, AUC).srt

11.1 KB

/7. Dealing with Real-World Data/

1. BiasVariance Tradeoff.mp4

69.5 MB

1. BiasVariance Tradeoff.srt

14.7 KB

10. Binning, Transforming, Encoding, Scaling, and Shuffling.mp4

50.2 MB

10. Binning, Transforming, Encoding, Scaling, and Shuffling.srt

14.6 KB

2. [Activity] K-Fold Cross-Validation to avoid overfitting.mp4

107.3 MB

2. [Activity] K-Fold Cross-Validation to avoid overfitting.srt

25.1 KB

3. Data Cleaning and Normalization.mp4

82.6 MB

3. Data Cleaning and Normalization.srt

17.5 KB

4. [Activity] Cleaning web log data.mp4

135.7 MB

4. [Activity] Cleaning web log data.srt

24.4 KB

5. Normalizing numerical data.mp4

40.1 MB

5. Normalizing numerical data.srt

7.8 KB

6. [Activity] Detecting outliers.mp4

38.1 MB

6. [Activity] Detecting outliers.srt

11.7 KB

7. Feature Engineering and the Curse of Dimensionality.mp4

43.7 MB

7. Feature Engineering and the Curse of Dimensionality.srt

12.1 KB

8. Imputation Techniques for Missing Data.mp4

51.4 MB

8. Imputation Techniques for Missing Data.srt

14.7 KB

9. Handling Unbalanced Data Oversampling, Undersampling, and SMOTE.mp4

38.1 MB

9. Handling Unbalanced Data Oversampling, Undersampling, and SMOTE.srt

10.1 KB

/8. Apache Spark Machine Learning on Big Data/

1. Warning about Java 11 and Spark 3!.html

0.6 KB

10. TF IDF.mp4

72.2 MB

10. TF IDF.srt

14.4 KB

11. [Activity] Searching Wikipedia with Spark.mp4

108.0 MB

11. [Activity] Searching Wikipedia with Spark.srt

13.2 KB

12. [Activity] Using the Spark 2.0 DataFrame API for MLLib.mp4

110.8 MB

12. [Activity] Using the Spark 2.0 DataFrame API for MLLib.srt

14.2 KB

2. Spark installation notes for MacOS and Linux users.html

3.7 KB

3. [Activity] Installing Spark - Part 1.mp4

87.7 MB

3. [Activity] Installing Spark - Part 1.srt

12.3 KB

3.1 winutils.exe.html

0.1 KB

4. [Activity] Installing Spark - Part 2.mp4

117.4 MB

4. [Activity] Installing Spark - Part 2.srt

10.8 KB

4.1 winutils.exe.html

0.1 KB

5. Spark Introduction.mp4

94.2 MB

5. Spark Introduction.srt

21.7 KB

6. Spark and the Resilient Distributed Dataset (RDD).mp4

103.3 MB

6. Spark and the Resilient Distributed Dataset (RDD).srt

25.0 KB

7. Introducing MLLib.mp4

57.4 MB

7. Introducing MLLib.srt

11.7 KB

8. Introduction to Decision Trees in Spark.mp4

140.5 MB

8. Introduction to Decision Trees in Spark.srt

28.8 KB

9. [Activity] K-Means Clustering in Spark.mp4

123.6 MB

9. [Activity] K-Means Clustering in Spark.srt

18.2 KB

/9. Experimental Design ML in the Real World/

1. Deploying Models to Real-Time Systems.mp4

34.6 MB

1. Deploying Models to Real-Time Systems.srt

15.8 KB

2. AB Testing Concepts.mp4

102.2 MB

2. AB Testing Concepts.srt

20.7 KB

3. T-Tests and P-Values.mp4

68.1 MB

3. T-Tests and P-Values.srt

13.5 KB

4. [Activity] Hands-on With T-Tests.mp4

85.6 MB

4. [Activity] Hands-on With T-Tests.srt

14.0 KB

5. Determining How Long to Run an Experiment.mp4

36.5 MB

5. Determining How Long to Run an Experiment.srt

8.5 KB

6. AB Test Gotchas.mp4

100.8 MB

6. AB Test Gotchas.srt

22.4 KB

/

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[FreeCourseWorld.Com].url

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Total files 224


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