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0
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0 B
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1. Bonus project.html
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HTML
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102.4 B
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1. Course Structure.mp4
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MP4
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13.9 MB
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1. Course Structure.srt
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SRT
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3.6 KB
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1. Extra Link.html
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HTML
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102.4 B
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1. Introduction to DNA Classifier.mp4
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MP4
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15.7 MB
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1. Introduction to DNA Classifier.srt
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SRT
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1.2 KB
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1. Introduction to the project.srt
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SRT
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1.2 KB
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1. Introduction.mp4
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MP4
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29.4 MB
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1. What is activation function.mp4
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MP4
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7.6 MB
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1. What is activation function.srt
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SRT
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1.5 KB
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1
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435.6 KB
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1. Introduction to the project.mp4
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MP4
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16.9 MB
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1. Introduction.srt
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SRT
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4 KB
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2. Bonus project.html
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HTML
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204.8 B
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2. How To Make The Most Out Of This Course.mp4
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MP4
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10 MB
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2. How To Make The Most Out Of This Course.srt
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SRT
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1.5 KB
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2. Importing data and Analysing data.mp4
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MP4
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68.6 MB
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2. Importing data and Analysing data.srt
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SRT
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9 KB
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2. Importing datas and libraries.mp4
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MP4
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52.4 MB
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2. Importing datas and libraries.srt
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SRT
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6 KB
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2. Importing library and data and Preprocessing data.mp4
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MP4
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137.7 MB
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2. Importing library and data and Preprocessing data.srt
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SRT
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16 KB
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2. Importing library and data.mp4
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MP4
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30.8 MB
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2. Thank you.mp4
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MP4
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23.1 MB
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2. Thank you.srt
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SRT
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1.7 KB
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2. What is sigmoid function.mp4
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MP4
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3.3 MB
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2. What is sigmoid function.srt
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SRT
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1.5 KB
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2
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283 KB
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10. Feature Scaling.mp4
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MP4
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33.2 MB
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10. Feature Scaling.srt
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SRT
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5.3 KB
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10. How to install Anaconda.mp4
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MP4
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26.2 MB
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10. How to install Anaconda.srt
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SRT
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2.4 KB
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10. Summary of the project.mp4
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MP4
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39 MB
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10. Summary of the project.srt
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SRT
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3.5 KB
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10. Testing accuracy.mp4
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MP4
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31.7 MB
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10. Testing accuracy.srt
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SRT
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4.7 KB
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10.1 Heart_disease_project.ipynb
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IPYNB
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299.7 KB
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11. Confusion matrix.mp4
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MP4
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69.6 MB
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11. Confusion matrix.srt
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SRT
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8.8 KB
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11. Important terms in Neural Network.mp4
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MP4
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105.9 MB
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11. Important terms in Neural Network.srt
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SRT
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11.1 KB
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11. Model building.mp4
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MP4
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56.1 MB
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11. Model building.srt
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SRT
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7.7 KB
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12. Analysing Results.mp4
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MP4
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108.5 MB
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12. Analysing Results.srt
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SRT
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12 KB
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12. ROC curve.mp4
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MP4
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44.2 MB
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12. ROC curve.srt
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SRT
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6 KB
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12.1 Diabetes_Udemy.ipynb
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IPYNB
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231 KB
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13. Further improvement.mp4
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MP4
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13.3 MB
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13. Further improvement.srt
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SRT
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4.1 KB
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13. Summary of the project.mp4
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MP4
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10.8 MB
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13. Summary of the project.srt
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SRT
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2.1 KB
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13.1 Taxi_fares_prediction_udemy.ipynb
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IPYNB
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798.4 KB
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14. Summary of the project.mp4
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MP4
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13.2 MB
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14. Summary of the project.srt
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SRT
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2.1 KB
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2. Important Parameters.mp4
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MP4
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84.4 MB
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2. Important Parameters.srt
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SRT
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6.8 KB
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2. Importing library and data.srt
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SRT
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4.5 KB
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2.1 diabetes.csv
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CSV
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23.3 KB
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3. AI in Healthcare.mp4
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MP4
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6.3 MB
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3. AI in Healthcare.srt
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SRT
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3 KB
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3. Data visualization.mp4
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MP4
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71.2 MB
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3. Data visualization.srt
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SRT
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8.8 KB
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3. Deep feedforward networks.mp4
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MP4
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42.7 MB
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3. Deep feedforward networks.srt
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SRT
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7.4 KB
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3. Fixing missing data.mp4
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MP4
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84.2 MB
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3. Fixing missing data.srt
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SRT
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9.8 KB
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3. Objective of this project.mp4
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MP4
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10.9 MB
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3. Objective of this project.srt
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SRT
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1.8 KB
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3. Showing data.mp4
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MP4
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11.3 MB
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3. Showing data.srt
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SRT
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1.7 KB
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3. Visualizing data.mp4
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MP4
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93 MB
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3. Visualizing data.srt
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SRT
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12.9 KB
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3. What is tanh function.mp4
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MP4
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2.4 MB
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3. What is tanh function.srt
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SRT
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1.1 KB
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3
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135 KB
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4. Generating a DNA sequence.mp4
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MP4
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140.9 MB
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4. Generating a DNA sequence.srt
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SRT
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17.2 KB
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4. Handling missing values.mp4
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MP4
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76 MB
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4. Handling missing values.srt
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SRT
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10.4 KB
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4. Importing library and data.mp4
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MP4
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66.5 MB
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4. Importing library and data.srt
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SRT
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7.1 KB
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4. Understanding Machine Learning Algorithm.mp4
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MP4
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84.6 MB
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4. Understanding Machine Learning Algorithm.srt
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SRT
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6.4 KB
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273.3 KB
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4. Splitting the dataset into training test and test set.mp4
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MP4
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47.6 MB
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4. Splitting the dataset into training test and test set.srt
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SRT
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5.5 KB
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4. What is Neuron.mp4
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MP4
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7.2 MB
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4. What is Neuron.srt
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SRT
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1.8 KB
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4. What is Rectified Linear Unit function.mp4
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MP4
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4.3 MB
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4. What is Rectified Linear Unit function.srt
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SRT
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1.7 KB
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4.1 Ch3.ClevelandData.xlsx
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XLSX
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27.9 KB
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5. Data standardization.mp4
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MP4
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50.2 MB
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5. Data standardization.srt
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SRT
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6.6 KB
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5. Exploratory analysis.mp4
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MP4
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42.1 MB
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5. Exploratory analysis.srt
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SRT
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5.6 KB
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5. Splitting the dataset into training test and test set.mp4
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MP4
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50.4 MB
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5. Splitting the dataset into training test and test set.srt
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SRT
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6.4 KB
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5. Training Neural Network.mp4
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MP4
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45.8 MB
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5. Training Neural Network.srt
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SRT
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5.4 KB
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5. Training model.mp4
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MP4
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102.3 MB
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5. Training model.srt
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SRT
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9.3 KB
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5. Visualizing geolocation data.mp4
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MP4
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151.5 MB
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5. Visualizing geolocation data.srt
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SRT
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16.7 KB
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5. What is Leaky ReLU function.mp4
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MP4
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2.2 MB
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5. What is Leaky ReLU function.srt
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SRT
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819.2 B
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5. What is deep Learning.mp4
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MP4
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18.5 MB
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5
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542.1 KB
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5. What is deep Learning.srt
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SRT
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1.4 KB
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6
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104.5 KB
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6. A comparison of categorical and binary problem.mp4
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MP4
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93.6 MB
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6. A comparison of categorical and binary problem.srt
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SRT
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9.9 KB
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6. Analysing Data.mp4
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MP4
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41.5 MB
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6. Analysing Data.srt
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SRT
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5.8 KB
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6. Handling missing data in Python.mp4
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MP4
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59.5 MB
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6. Handling missing data in Python.srt
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SRT
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11.2 KB
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6. Make a Prediction.mp4
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MP4
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126.5 MB
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6. Make a Prediction.srt
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SRT
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12.6 KB
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6. Scoring method and results.mp4
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MP4
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146.7 MB
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6. Scoring method and results.srt
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SRT
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12.2 KB
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6. Splitting the data into training, testing, and validation sets.mp4
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MP4
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112.9 MB
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6. Splitting the data into training, testing, and validation sets.srt
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SRT
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10.6 KB
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6. What is ANN.mp4
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MP4
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18.3 MB
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6. What is ANN.srt
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SRT
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4.2 KB
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6. What is The Exponential Linear Unit Function.mp4
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MP4
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1.9 MB
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6. What is The Exponential Linear Unit Function.srt
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SRT
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819.2 B
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7. Data scaling.mp4
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MP4
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65.3 MB
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7. Data scaling.srt
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SRT
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9.8 KB
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7. Handling missing data and anomalies in Python.mp4
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MP4
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111.6 MB
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7. Handling missing data and anomalies in Python.srt
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SRT
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18.5 KB
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7. Model building.srt
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SRT
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5.3 KB
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7. Summary of the project.mp4
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MP4
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8.3 MB
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7
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400.8 KB
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7. Model building.mp4
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MP4
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39.1 MB
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7. Summary of the project.srt
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SRT
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1.7 KB
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7. What is The Swish function.mp4
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MP4
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3.7 MB
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7. What is The Swish function.srt
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SRT
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1.9 KB
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7. What is keras.mp4
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MP4
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34.1 MB
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7. What is keras.srt
|
SRT
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6.1 KB
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7.1 Breast_cancer_projects.ipynb
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IPYNB
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369.1 KB
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7.1 DNA CLASSIFICATION.ipynb
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IPYNB
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41.7 KB
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7.1 Heart Disease Prediction with Neural Networks.ipynb
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IPYNB
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130.8 KB
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8. Data visualization.mp4
|
MP4
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72.5 MB
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8. Data visualization.srt
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SRT
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9.4 KB
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8
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481.5 KB
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8. Introduction to Pandas and visualization.mp4
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MP4
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61.1 MB
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8. Introduction to Pandas and visualization.srt
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SRT
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11.3 KB
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8. Model compilation.mp4
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MP4
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30.2 MB
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8. Model compilation.srt
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SRT
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3.8 KB
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8. Temporal features.mp4
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MP4
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30.4 MB
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8. Temporal features.srt
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SRT
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4.4 KB
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8. What is The softmax function.mp4
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MP4
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2.4 MB
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8. What is The softmax function.srt
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SRT
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1.2 KB
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9. Data Preprocessing by Pandas.mp4
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MP4
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60.2 MB
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9. Data Preprocessing by Pandas.srt
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SRT
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9.7 KB
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9. Geolocation features.mp4
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MP4
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92.2 MB
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9. Geolocation features.srt
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SRT
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14.7 KB
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9
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66.2 KB
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9. Model training.mp4
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MP4
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14.7 MB
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9. Model training.srt
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SRT
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2 KB
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9. Splitting training set into test set and Evaluating the model.mp4
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MP4
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207.7 MB
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9. Splitting training set into test set and Evaluating the model.srt
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SRT
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24.5 KB
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9. Time to code all the activation functions.mp4
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MP4
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36.9 MB
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9. Time to code all the activation functions.srt
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SRT
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6.8 KB
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9.1 Activation_function.ipynb
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IPYNB
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2.5 KB
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9.1 Pandas.ipynb
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IPYNB
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62.3 KB
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TutsNode.com.txt
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TXT
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102.4 B
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[TGx]Downloaded from torrentgalaxy.to .txt
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TXT
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614.4 B
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10
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765 KB
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