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| 1. [Activity] Linear Regression.mp4 |
100.46Мб |
| 1. [Activity] Linear Regression.srt |
25.70Кб |
| 1. BiasVariance Tradeoff.mp4 |
66.31Мб |
| 1. BiasVariance Tradeoff.srt |
14.40Кб |
| 1. Deep Learning Pre-Requisites.mp4 |
74.17Мб |
| 1. Deep Learning Pre-Requisites.srt |
21.52Кб |
| 1. Deploying Models to Real-Time Systems.mp4 |
33.04Мб |
| 1. Deploying Models to Real-Time Systems.srt |
15.42Кб |
| 1. Introduction.mp4 |
59.60Мб |
| 1. Introduction.srt |
4.75Кб |
| 1. K-Nearest-Neighbors Concepts.mp4 |
40.28Мб |
| 1. K-Nearest-Neighbors Concepts.srt |
8.95Кб |
| 1. More to Explore.mp4 |
64.06Мб |
| 1. More to Explore.srt |
7.24Кб |
| 1. Supervised vs. Unsupervised Learning, and TrainTest.mp4 |
98.61Мб |
| 1. Supervised vs. Unsupervised Learning, and TrainTest.srt |
20.90Кб |
| 1. Types of Data.mp4 |
77.25Мб |
| 1. Types of Data.srt |
16.24Кб |
| 1. User-Based Collaborative Filtering.mp4 |
86.37Мб |
| 1. User-Based Collaborative Filtering.srt |
19.38Кб |
| 1. Warning about Java 11 and Spark 2.4!.html |
650б |
| 1. Your final project assignment.mp4 |
51.63Мб |
| 1. Your final project assignment.srt |
11.56Кб |
| 10. [Activity] Covariance and Correlation.mp4 |
116.74Мб |
| 10. [Activity] Covariance and Correlation.srt |
25.91Кб |
| 10. [Activity] LINUX Installing Graphviz.mp4 |
7.05Мб |
| 10. [Activity] LINUX Installing Graphviz.srt |
1.11Кб |
| 10. [Activity] Python Basics, Part 4 [Optional].mp4 |
21.12Мб |
| 10. [Activity] Python Basics, Part 4 [Optional].srt |
6.00Кб |
| 10. [Activity] Using Keras to Predict Political Affiliations.mp4 |
88.20Мб |
| 10. [Activity] Using Keras to Predict Political Affiliations.srt |
21.14Кб |
| 10. Binning, Transforming, Encoding, Scaling, and Shuffling.mp4 |
47.91Мб |
| 10. Binning, Transforming, Encoding, Scaling, and Shuffling.srt |
14.21Кб |
| 10. TF IDF.mp4 |
68.85Мб |
| 10. TF IDF.srt |
14.03Кб |
| 11. [Activity] Searching Wikipedia with Spark.mp4 |
102.99Мб |
| 11. [Activity] Searching Wikipedia with Spark.srt |
12.85Кб |
| 11. [Exercise] Conditional Probability.mp4 |
125.14Мб |
| 11. [Exercise] Conditional Probability.srt |
28.41Кб |
| 11. Convolutional Neural Networks (CNN's).mp4 |
93.09Мб |
| 11. Convolutional Neural Networks (CNN's).srt |
19.86Кб |
| 11. Decision Trees Concepts.mp4 |
86.53Мб |
| 11. Decision Trees Concepts.srt |
21.10Кб |
| 11. Introducing the Pandas Library [Optional].mp4 |
123.10Мб |
| 11. Introducing the Pandas Library [Optional].srt |
18.05Кб |
| 12. [Activity] Decision Trees Predicting Hiring Decisions.mp4 |
95.95Мб |
| 12. [Activity] Decision Trees Predicting Hiring Decisions.srt |
22.45Кб |
| 12. [Activity] Using CNN's for handwriting recognition.mp4 |
69.56Мб |
| 12. [Activity] Using CNN's for handwriting recognition.srt |
13.76Кб |
| 12. [Activity] Using the Spark 2.0 DataFrame API for MLLib.mp4 |
105.68Мб |
| 12. [Activity] Using the Spark 2.0 DataFrame API for MLLib.srt |
13.91Кб |
| 12. Exercise Solution Conditional Probability of Purchase by Age.mp4 |
22.00Мб |
| 12. Exercise Solution Conditional Probability of Purchase by Age.srt |
3.99Кб |
| 13. Bayes' Theorem.mp4 |
58.90Мб |
| 13. Bayes' Theorem.srt |
11.49Кб |
| 13. Ensemble Learning.mp4 |
65.21Мб |
| 13. Ensemble Learning.srt |
14.55Кб |
| 13. Recurrent Neural Networks (RNN's).mp4 |
69.17Мб |
| 13. Recurrent Neural Networks (RNN's).srt |
18.48Кб |
| 14. [Activity] Using a RNN for sentiment analysis.mp4 |
81.36Мб |
| 14. [Activity] Using a RNN for sentiment analysis.srt |
16.82Кб |
| 14. Support Vector Machines (SVM) Overview.mp4 |
44.74Мб |
| 14. Support Vector Machines (SVM) Overview.srt |
9.88Кб |
| 15. [Activity] Transfer Learning.mp4 |
115.26Мб |
| 15. [Activity] Transfer Learning.srt |
21.53Кб |
| 15. [Activity] Using SVM to cluster people using scikit-learn.mp4 |
43.94Мб |
| 15. [Activity] Using SVM to cluster people using scikit-learn.srt |
14.85Кб |
| 16. Tuning Neural Networks Learning Rate and Batch Size Hyperparameters.mp4 |
18.43Мб |
| 16. Tuning Neural Networks Learning Rate and Batch Size Hyperparameters.srt |
8.29Кб |
| 17. Deep Learning Regularization with Dropout and Early Stopping.mp4 |
33.64Мб |
| 17. Deep Learning Regularization with Dropout and Early Stopping.srt |
11.97Кб |
| 18. The Ethics of Deep Learning.mp4 |
128.24Мб |
| 18. The Ethics of Deep Learning.srt |
19.84Кб |
| 19. Learning More about Deep Learning.mp4 |
38.64Мб |
| 19. Learning More about Deep Learning.srt |
3.14Кб |
| 2. [Activity] K-Fold Cross-Validation to avoid overfitting.mp4 |
102.34Мб |
| 2. [Activity] K-Fold Cross-Validation to avoid overfitting.srt |
24.54Кб |
| 2. [Activity] Polynomial Regression.mp4 |
66.77Мб |
| 2. [Activity] Polynomial Regression.srt |
17.59Кб |
| 2. [Activity] Using KNN to predict a rating for a movie.mp4 |
142.06Мб |
| 2. [Activity] Using KNN to predict a rating for a movie.srt |
28.48Кб |
| 2. [Activity] Using TrainTest to Prevent Overfitting a Polynomial Regression.mp4 |
58.14Мб |
| 2. [Activity] Using TrainTest to Prevent Overfitting a Polynomial Regression.srt |
13.11Кб |
| 2. AB Testing Concepts.mp4 |
97.49Мб |
| 2. AB Testing Concepts.srt |
97.49Мб |
| 2. Don't Forget to Leave a Rating!.html |
564б |
| 2. Final project review.mp4 |
98.50Мб |
| 2. Final project review.srt |
24.51Кб |
| 2. Item-Based Collaborative Filtering.mp4 |
75.00Мб |
| 2. Item-Based Collaborative Filtering.srt |
19.99Кб |
| 2. Mean, Median, Mode.mp4 |
56.15Мб |
| 2. Mean, Median, Mode.srt |
12.95Кб |
| 2. Spark installation notes for MacOS and Linux users.html |
3.48Кб |
| 2. The History of Artificial Neural Networks.mp4 |
79.98Мб |
| 2. The History of Artificial Neural Networks.srt |
19.07Кб |
| 2. Udemy 101 Getting the Most From This Course.mp4 |
19.77Мб |
| 2. Udemy 101 Getting the Most From This Course.srt |
4.04Кб |
| 3. [Activity] Deep Learning in the Tensorflow Playground.mp4 |
141.58Мб |
| 3. [Activity] Deep Learning in the Tensorflow Playground.srt |
141.62Мб |
| 3. [Activity] Finding Movie Similarities.mp4 |
107.83Мб |
| 3. [Activity] Finding Movie Similarities.srt |
20.08Кб |
| 3. [Activity] Installing Spark - Part 1.mp4 |
83.63Мб |
| 3. [Activity] Installing Spark - Part 1.srt |
12.04Кб |
| 3. [Activity] Multiple Regression, and Predicting Car Prices.mp4 |
73.85Мб |
| 3. [Activity] Multiple Regression, and Predicting Car Prices.srt |
21.13Кб |
| 3. [Activity] Using mean, median, and mode in Python.mp4 |
61.93Мб |
| 3. [Activity] Using mean, median, and mode in Python.srt |
15.01Кб |
| 3.1 winutils.exe.html |
108б |
| 3. Bayesian Methods Concepts.mp4 |
40.73Мб |
| 3. Bayesian Methods Concepts.srt |
8.83Кб |
| 3. Bonus Lecture More courses to explore!.html |
7.32Кб |
| 3. Data Cleaning and Normalization.mp4 |
78.75Мб |
| 3. Data Cleaning and Normalization.srt |
17.08Кб |
| 3. Dimensionality Reduction; Principal Component Analysis.mp4 |
67.74Мб |
| 3. Dimensionality Reduction; Principal Component Analysis.srt |
12.32Кб |
| 3. Installation Getting Started.html |
265б |
| 3. T-Tests and P-Values.mp4 |
64.92Мб |
| 3. T-Tests and P-Values.srt |
13.16Кб |
| 4. [Activity] Cleaning web log data.mp4 |
129.38Мб |
| 4. [Activity] Cleaning web log data.srt |
23.78Кб |
| 4. [Activity] Hands-on With T-Tests.mp4 |
81.62Мб |
| 4. [Activity] Hands-on With T-Tests.srt |
81.63Мб |
| 4. [Activity] Implementing a Spam Classifier with Naive Bayes.mp4 |
89.09Мб |
| 4. [Activity] Implementing a Spam Classifier with Naive Bayes.srt |
17.42Кб |
| 4. [Activity] Improving the Results of Movie Similarities.mp4 |
94.86Мб |
| 4. [Activity] Improving the Results of Movie Similarities.srt |
16.78Кб |
| 4. [Activity] Installing Spark - Part 2.mp4 |
111.98Мб |
| 4. [Activity] Installing Spark - Part 2.srt |
10.59Кб |
| 4. [Activity] PCA Example with the Iris data set.mp4 |
109.73Мб |
| 4. [Activity] PCA Example with the Iris data set.srt |
21.20Кб |
| 4. [Activity] Variation and Standard Deviation.mp4 |
110.86Мб |
| 4. [Activity] Variation and Standard Deviation.srt |
25.83Кб |
| 4. [Activity] WINDOWS Installing and Using Anaconda & Course Materials.mp4 |
102.76Мб |
| 4. [Activity] WINDOWS Installing and Using Anaconda & Course Materials.srt |
18.88Кб |
| 4.1 winutils.exe.html |
108б |
| 4. Deep Learning Details.mp4 |
64.22Мб |
| 4. Deep Learning Details.srt |
64.25Мб |
| 4. Multi-Level Models.mp4 |
47.47Мб |
| 4. Multi-Level Models.srt |
10.66Кб |
| 5. [Activity] MAC Installing and Using Anaconda & Course Materials.mp4 |
96.53Мб |
| 5. [Activity] MAC Installing and Using Anaconda & Course Materials.srt |
14.48Кб |
| 5. [Activity] Making Movie Recommendations to People.mp4 |
132.55Мб |
| 5. [Activity] Making Movie Recommendations to People.srt |
22.61Кб |
| 5. Data Warehousing Overview ETL and ELT.mp4 |
103.33Мб |
| 5. Data Warehousing Overview ETL and ELT.srt |
19.74Кб |
| 5. Determining How Long to Run an Experiment.mp4 |
34.84Мб |
| 5. Determining How Long to Run an Experiment.srt |
8.34Кб |
| 5. Introducing Tensorflow.mp4 |
86.27Мб |
| 5. Introducing Tensorflow.srt |
22.51Кб |
| 5. K-Means Clustering.mp4 |
71.94Мб |
| 5. K-Means Clustering.srt |
17.20Кб |
| 5. Normalizing numerical data.mp4 |
38.20Мб |
| 5. Normalizing numerical data.srt |
7.65Кб |
| 5. Probability Density Function; Probability Mass Function.mp4 |
30.07Мб |
| 5. Probability Density Function; Probability Mass Function.srt |
7.59Кб |
| 5. Spark Introduction.mp4 |
89.86Мб |
| 5. Spark Introduction.srt |
21.21Кб |
| 6. [Activity] Clustering people based on income and age.mp4 |
57.29Мб |
| 6. [Activity] Clustering people based on income and age.srt |
11.55Кб |
| 6. [Activity] Detecting outliers.mp4 |
36.32Мб |
| 6. [Activity] Detecting outliers.srt |
11.44Кб |
| 6. [Activity] LINUX Installing and Using Anaconda & Course Materials.mp4 |
80.21Мб |
| 6. [Activity] LINUX Installing and Using Anaconda & Course Materials.srt |
14.66Кб |
| 6. [Exercise] Improve the recommender's results.mp4 |
84.23Мб |
| 6. [Exercise] Improve the recommender's results.srt |
13.20Кб |
| 6.1 Cat and Mouse Example.html |
140б |
| 6.2 Pac-Man Example.html |
145б |
| 6.3 Python Markov Decision Process Toolbox.html |
119б |
| 6. AB Test Gotchas.mp4 |
96.10Мб |
| 6. AB Test Gotchas.srt |
21.88Кб |
| 6. Common Data Distributions.mp4 |
75.37Мб |
| 6. Common Data Distributions.srt |
16.08Кб |
| 6. Important note about Tensorflow 2.html |
1000б |
| 6. Reinforcement Learning.mp4 |
132.26Мб |
| 6. Reinforcement Learning.srt |
28.50Кб |
| 6. Spark and the Resilient Distributed Dataset (RDD).mp4 |
98.51Мб |
| 6. Spark and the Resilient Distributed Dataset (RDD).srt |
24.41Кб |
| 7. [Activity] Percentiles and Moments.mp4 |
114.04Мб |
| 7. [Activity] Percentiles and Moments.srt |
28.33Кб |
| 7. [Activity] Reinforcement Learning & Q-Learning with Gym.mp4 |
77.96Мб |
| 7. [Activity] Reinforcement Learning & Q-Learning with Gym.srt |
22.49Кб |
| 7. [Activity] Using Tensorflow, Part 1.mp4 |
72.69Мб |
| 7. [Activity] Using Tensorflow, Part 1.srt |
13.84Кб |
| 7. Feature Engineering and the Curse of Dimensionality.mp4 |
41.71Мб |
| 7. Feature Engineering and the Curse of Dimensionality.srt |
11.83Кб |
| 7. Introducing MLLib.mp4 |
54.74Мб |
| 7. Introducing MLLib.srt |
11.46Кб |
| 7. Measuring Entropy.mp4 |
34.97Мб |
| 7. Measuring Entropy.srt |
6.90Кб |
| 7. Python Basics, Part 1 [Optional].mp4 |
32.98Мб |
| 7. Python Basics, Part 1 [Optional].srt |
7.76Кб |
| 8. [Activity] A Crash Course in matplotlib.mp4 |
129.35Мб |
| 8. [Activity] A Crash Course in matplotlib.srt |
28.57Кб |
| 8. [Activity] Python Basics, Part 2 [Optional].mp4 |
20.63Мб |
| 8. [Activity] Python Basics, Part 2 [Optional].srt |
7.63Кб |
| 8. [Activity] Using Tensorflow, Part 2.mp4 |
108.64Мб |
| 8. [Activity] Using Tensorflow, Part 2.srt |
23.35Кб |
| 8. [Activity] WINDOWS Installing Graphviz.mp4 |
2.06Мб |
| 8. [Activity] WINDOWS Installing Graphviz.srt |
689б |
| 8. Imputation Techniques for Missing Data.mp4 |
49.02Мб |
| 8. Imputation Techniques for Missing Data.srt |
14.31Кб |
| 8. Introduction to Decision Trees in Spark.mp4 |
134.02Мб |
| 8. Introduction to Decision Trees in Spark.srt |
28.10Кб |
| 8. Understanding a Confusion Matrix.mp4 |
14.84Мб |
| 8. Understanding a Confusion Matrix.srt |
9.71Кб |
| 9. [Activity] Advanced Visualization with Seaborn.mp4 |
147.81Мб |
| 9. [Activity] Advanced Visualization with Seaborn.srt |
29.96Кб |
| 9. [Activity] Introducing Keras.mp4 |
92.05Мб |
| 9. [Activity] Introducing Keras.srt |
23.75Кб |
| 9. [Activity] K-Means Clustering in Spark.mp4 |
117.86Мб |
| 9. [Activity] K-Means Clustering in Spark.srt |
17.73Кб |
| 9. [Activity] MAC Installing Graphviz.mp4 |
14.83Мб |
| 9. [Activity] MAC Installing Graphviz.srt |
1.26Кб |
| 9. [Activity] Python Basics, Part 3 [Optional].mp4 |
10.09Мб |
| 9. [Activity] Python Basics, Part 3 [Optional].srt |
4.24Кб |
| 9. Handling Unbalanced Data Oversampling, Undersampling, and SMOTE.mp4 |
36.34Мб |
| 9. Handling Unbalanced Data Oversampling, Undersampling, and SMOTE.srt |
9.88Кб |
| 9. Measuring Classifiers (Precision, Recall, F1, ROC, AUC).mp4 |
25.79Мб |
| 9. Measuring Classifiers (Precision, Recall, F1, ROC, AUC).srt |
10.82Кб |
| GetFreeCourses.Co.url |
116б |
| How you can help GetFreeCourses.Co.txt |
182б |