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1. AB Testing Concepts.mp4
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1. BiasVariance Tradeoff.mp4
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1. Deep Learning Pre-Requisites.mp4
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1. Introduction.mp4
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1. K-Nearest-Neighbors Concepts.mp4
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1. More to Explore.mp4
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1. Supervised vs. Unsupervised Learning, and TrainTest.mp4
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1. Types of Data.mp4
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1. User-Based Collaborative Filtering.mp4
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1. Warning about Java 10!.html
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1. Your final project assignment.mp4
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1. [Activity] Linear Regression.mp4
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10. Convolutional Neural Networks (CNN's).mp4
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10. Convolutional Neural Networks (CNN's).vtt
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10. [Activity] Decision Trees Predicting Hiring Decisions.mp4
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10. [Activity] Decision Trees Predicting Hiring Decisions.vtt
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10. [Activity] Searching Wikipedia with Spark.mp4
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10. [Activity] Searching Wikipedia with Spark.vtt
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10. [Exercise] Conditional Probability.mp4
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10. [Exercise] Conditional Probability.mp4.jpg
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10. [Exercise] Conditional Probability.vtt
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11. Ensemble Learning.mp4
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11. Exercise Solution Conditional Probability of Purchase by Age.mp4
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11. [Activity] Using CNN's for handwriting recognition.mp4
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11. [Activity] Using the Spark 2.0 DataFrame API for MLLib.mp4
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11. [Activity] Using the Spark 2.0 DataFrame API for MLLib.vtt
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12. Bayes' Theorem.mp4
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12. Recurrent Neural Networks (RNN's).mp4
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12. Support Vector Machines (SVM) Overview.mp4
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13. [Activity] Using SVM to cluster people using scikit-learn.mp4
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13. [Activity] Using SVM to cluster people using scikit-learn.vtt
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13. [Activity] Using a RNN for sentiment analysis.mp4
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14. The Ethics of Deep Learning.mp4
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14. The Ethics of Deep Learning.vtt
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15. Learning More about Deep Learning.mp4
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2. Don't Forget to Leave a Rating!.html
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2. Final project review.mp4
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2. Item-Based Collaborative Filtering.mp4
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2. Mean, Median, Mode.mp4
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2. T-Tests and P-Values.mp4
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2. The History of Artificial Neural Networks.mp4
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80 MB
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2. Udemy 101 Getting the Most From This Course.mp4
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19.8 MB
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2. Udemy 101 Getting the Most From This Course.vtt
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2. [Activity] Installing Spark - Part 1.mp4
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2. [Activity] K-Fold Cross-Validation to avoid overfitting.mp4
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102.3 MB
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2. [Activity] K-Fold Cross-Validation to avoid overfitting.vtt
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2. [Activity] Polynomial Regression.mp4
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66.8 MB
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2. [Activity] Polynomial Regression.vtt
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2. [Activity] Using KNN to predict a rating for a movie.mp4
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142.1 MB
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2. [Activity] Using KNN to predict a rating for a movie.vtt
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2. [Activity] Using TrainTest to Prevent Overfitting a Polynomial Regression.mp4
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58.1 MB
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2. [Activity] Using TrainTest to Prevent Overfitting a Polynomial Regression.vtt
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2.1 winutils.exe.html
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3. Bayesian Methods Concepts.mp4
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3. Bonus Lecture Discounts on my Spark and MapReduce courses!.mp4
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48.4 MB
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3. Bonus Lecture Discounts on my Spark and MapReduce courses!.vtt
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3. Data Cleaning and Normalization.mp4
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3. Dimensionality Reduction; Principal Component Analysis.mp4
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3. [Activity] Deep Learning in the Tensorflow Playground.mp4
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141.6 MB
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3. [Activity] Deep Learning in the Tensorflow Playground.vtt
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3. [Activity] Finding Movie Similarities.mp4
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3. [Activity] Finding Movie Similarities.vtt
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3. [Activity] Getting What You Need.mp4
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3. [Activity] Hands-on With T-Tests.mp4
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3. [Activity] Hands-on With T-Tests.vtt
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3. [Activity] Installing Spark - Part 2.mp4
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3. [Activity] Multivariate Regression, and Predicting Car Prices.mp4
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123.8 MB
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3. [Activity] Multivariate Regression, and Predicting Car Prices.vtt
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3. [Activity] Using mean, median, and mode in Python.mp4
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92.7 MB
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3. [Activity] Using mean, median, and mode in Python.vtt
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3.1 Course Facebook Group.html
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3.1 Get this course in printed book form!.html
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3.1 winutils.exe.html
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3.2 Become a mentor.html
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3.3 My website!.html
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4. Deep Learning Details.mp4
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4. Determining How Long to Run an Experiment.mp4
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4. Multi-Level Models.mp4
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4. Spark Introduction.mp4
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4. [Activity] Cleaning web log data.mp4
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4. [Activity] Implementing a Spam Classifier with Naive Bayes.mp4
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4. [Activity] Improving the Results of Movie Similarities.mp4
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4. [Activity] Installing Enthought Canopy.mp4
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109 MB
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4. [Activity] PCA Example with the Iris data set.mp4
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4. [Activity] Variation and Standard Deviation.mp4
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110.8 MB
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4. [Activity] Variation and Standard Deviation.vtt
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4.1 Enthought Canopy website.html
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5. AB Test Gotchas.mp4
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5. Data Warehousing Overview ETL and ELT.mp4
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5. Introducing Tensorflow.mp4
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5. K-Means Clustering.mp4
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5. Normalizing numerical data.mp4
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5. Probability Density Function; Probability Mass Function.mp4
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5. Python Basics, Part 1 [Optional].mp4
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5. Spark and the Resilient Distributed Dataset (RDD).mp4
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5. [Activity] Making Movie Recommendations to People.mp4
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132.6 MB
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6. Common Data Distributions.mp4
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75.4 MB
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6. Common Data Distributions.vtt
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6. Introducing MLLib.mp4
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54.7 MB
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6. Introducing MLLib.vtt
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6. Reinforcement Learning.mp4
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132.3 MB
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6. Reinforcement Learning.vtt
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6. [Activity] Clustering people based on income and age.mp4
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57.3 MB
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6. [Activity] Clustering people based on income and age.vtt
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6. [Activity] Detecting outliers.mp4
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6. [Activity] Detecting outliers.vtt
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6. [Activity] Python Basics, Part 2 [Optional].mp4
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77.2 MB
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6. [Activity] Python Basics, Part 2 [Optional].vtt
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6. [Activity] Using Tensorflow, Part 1.mp4
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102.3 MB
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6. [Activity] Using Tensorflow, Part 1.vtt
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6. [Exercise] Improve the recommender's results.mp4
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84.2 MB
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6. [Exercise] Improve the recommender's results.vtt
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12 KB
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6.1 Pac-Man Example.html
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6.2 Python Markov Decision Process Toolbox.html
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6.3 Cat and Mouse Example.html
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7. Measuring Entropy.mp4
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35 MB
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7. Measuring Entropy.vtt
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7. Running Python Scripts [Optional].mp4
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7. Running Python Scripts [Optional].vtt
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7. [Activity] Decision Trees in Spark.mp4
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193.2 MB
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7. [Activity] Decision Trees in Spark.mp4.jpg
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7. [Activity] Percentiles and Moments.mp4
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114 MB
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7. [Activity] Percentiles and Moments.vtt
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7. [Activity] Using Tensorflow, Part 2.mp4
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133.6 MB
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7. [Activity] Using Tensorflow, Part 2.vtt
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8. Introducing the Pandas Library [Optional].mp4
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MP4
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127.9 MB
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8. Introducing the Pandas Library [Optional].vtt
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8. [Activity] A Crash Course in matplotlib.mp4
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129.3 MB
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8. [Activity] A Crash Course in matplotlib.vtt
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25.8 KB
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8. [Activity] Install GraphViz.html
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1.5 KB
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8. [Activity] Introducing Keras.mp4
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107.5 MB
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8. [Activity] Introducing Keras.vtt
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8. [Activity] K-Means Clustering in Spark.mp4
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MP4
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133.8 MB
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8. [Activity] K-Means Clustering in Spark.vtt
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20.2 KB
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9. Decision Trees Concepts.mp4
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MP4
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86.5 MB
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9. Decision Trees Concepts.vtt
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19.1 KB
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9. TF IDF.mp4
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MP4
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68.8 MB
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9. TF IDF.vtt
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9. [Activity] Covariance and Correlation.mp4
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MP4
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116.7 MB
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9. [Activity] Covariance and Correlation.vtt
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23.4 KB
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9. [Activity] Using Keras to Predict Political Affiliations.mp4
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MP4
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104.3 MB
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9. [Activity] Using Keras to Predict Political Affiliations.vtt
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26.1 KB
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Course Downloaded from coursedrive.net.txt
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409.6 B
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ReadMe.txt
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409.6 B
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Visit Coursedrive.net.url
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URL
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102.4 B
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Visit DazX Blog on SAnet.ST for more.url
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URL
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