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1. Bayes Theorem.mp4
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MP4
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87.3 MB
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1. Binary Classification Introduction.mp4
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MP4
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85.5 MB
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1. Biological Neural Network.mp4
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MP4
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28.4 MB
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1. Boosting Introduction.mp4
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MP4
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120.4 MB
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1. CODE - Decision Tree Node.mp4
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MP4
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61.2 MB
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1. Course Overview.mp4
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MP4
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49.6 MB
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1. Curse of Dimensionality.mp4
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MP4
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17 MB
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1. Decision Trees Introduction.mp4
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MP4
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78 MB
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1. Ensemble Learning.mp4
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MP4
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69.3 MB
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1. Introduction to Linear Regression.mp4
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MP4
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26.6 MB
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1. Introduction to PCA.mp4
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MP4
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63.4 MB
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1. Introduction.mp4
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MP4
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45 MB
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1. K-Means Algorithm.mp4
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MP4
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60.1 MB
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1. Multinomial Naive Bayes.mp4
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MP4
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141.1 MB
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1. OpenCV - Working with Images.mp4
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MP4
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34 MB
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1. Project Overview.mp4
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MP4
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122.4 MB
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1. Supervised Learning Introduction.mp4
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MP4
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78.3 MB
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1.1 Dataset Link.html
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HTML
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102.4 B
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1.1 titanic_train.csv
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CSV
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58.9 KB
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10. A Note about Shapes.mp4
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MP4
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30.1 MB
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10. CODE - Likelihood.mp4
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MP4
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166.5 MB
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10. CODE - Model Building.mp4
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MP4
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45.8 MB
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10. Code 01 - Data Generation.mp4
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MP4
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68.2 MB
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10. Code 05 - Training Loop.mp4
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MP4
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61.6 MB
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10. Code Repository.html
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HTML
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204.8 B
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10. Decision Trees for Regression.mp4
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MP4
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89.5 MB
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10. Predictions.mp4
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MP4
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30.2 MB
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11. CODE - Model Training and Testing.mp4
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MP4
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85 MB
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11. CODE - Prediction.mp4
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MP4
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71.4 MB
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11. Code 02 - Data Normalisation.mp4
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MP4
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170.9 MB
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11. Code 06 - Evaluation.mp4
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MP4
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50.9 MB
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11. Code 06 - Visualise Decision Boundary.mp4
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MP4
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43.1 MB
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11. Decision Tree Code - Sklearn.mp4
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MP4
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36.7 MB
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12. Code 03 - Train Test Split.mp4
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MP4
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89.3 MB
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12. Code 07 - Predictions & Accuracy.mp4
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MP4
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55.5 MB
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12. Implementing Naive Bayes - Sklearn.mp4
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MP4
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111.5 MB
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12. Linear Regression using Sk-Learn.mp4
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MP4
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35.4 MB
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13. Code 04 - Modelling.mp4
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MP4
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118.1 MB
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13. Logistic Regression using Sk-Learn.mp4
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MP4
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29.5 MB
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14. Code 05 - Predictions.mp4
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MP4
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54.1 MB
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14. Multiclass Classification One Vs Rest.mp4
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MP4
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72.4 MB
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15. Multiclass Classification One Vs One.mp4
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MP4
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33.5 MB
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15. R2 Score.mp4
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MP4
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139.3 MB
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16. Code 06 - Evaluation.mp4
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MP4
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28.8 MB
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17. Code 07 - Visualisation.mp4
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MP4
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103.4 MB
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18. Code 08 - Trajectory [Optional].mp4
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MP4
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93.9 MB
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2. A Neuron.mp4
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MP4
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34.1 MB
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2. Artificial Intelligence.mp4
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MP4
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48.6 MB
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2. Bagging Model.mp4
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MP4
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128.8 MB
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2. Boosting Intuition.mp4
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MP4
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133.5 MB
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2. CODE - Train Decision Tree.mp4
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MP4
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119.7 MB
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2. Code 01 - Data Prep.mp4
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MP4
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18.6 MB
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2. Conceptual Overview of PCA.mp4
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MP4
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140.9 MB
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2. Data Clearning.mp4
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MP4
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157.9 MB
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2. Decision Trees Example.mp4
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MP4
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137.4 MB
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2. Derivation of Bayes Theorem.mp4
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MP4
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74.8 MB
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2. Exploratory Data Analysis.mp4
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MP4
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103.3 MB
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2. Feature Selection Vs. Feature Extraction.mp4
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MP4
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15.1 MB
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2. Hypothesis.mp4
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MP4
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28.8 MB
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2. KNN Idea.mp4
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MP4
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34.5 MB
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2. Laplace Smoothing.mp4
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MP4
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91.5 MB
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2. Notation.mp4
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MP4
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105.3 MB
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2. OpenCV - Video Input from WebCam.mp4
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MP4
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34.2 MB
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2. Reading Images.mp4
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MP4
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24.2 MB
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2. Supervised Learning Example.mp4
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MP4
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198.1 MB
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2. The Data.mp4
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MP4
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48.6 MB
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3. Bayes Theorem Question.mp4
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MP4
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145 MB
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3. Boosting Mathematical Formulation.mp4
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MP4
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211.5 MB
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3. CODE - Assign Target Variable to Each Node.mp4
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MP4
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59.9 MB
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3. Code 02 - Init Centers.mp4
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MP4
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65.7 MB
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3. Data Visualisation.mp4
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MP4
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52.5 MB
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3. Entropy.mp4
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MP4
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118.4 MB
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3. Exploratory Data Analysis - II.mp4
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MP4
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79 MB
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3. Filter Method.mp4
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MP4
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23.5 MB
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3. Finding Clusters.mp4
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MP4
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53.9 MB
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3. How does a perceptron Learns.mp4
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MP4
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42.8 MB
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3. Hypothesis Function.mp4
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MP4
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272.3 MB
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3. Hypothesis.mp4
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MP4
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95.1 MB
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3. KNN Data Prep.mp4
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MP4
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29.2 MB
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3. Loss Function.mp4
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MP4
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33.2 MB
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3. Machine Learning.mp4
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MP4
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67 MB
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3. Maximising Variance.mp4
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MP4
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178 MB
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3. Multinomial Naive Bayes Example.mp4
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MP4
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179.2 MB
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3. Object Detection using Haarcascades.mp4
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MP4
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79.6 MB
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3. Structured Data.mp4
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MP4
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31.9 MB
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3. Unsupervised Learning.mp4
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MP4
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94 MB
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3. Why Bagging Helps.mp4
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MP4
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142.6 MB
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3. WordCloud.mp4
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MP4
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106.2 MB
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4. Bernoulli Naive Bayes.mp4
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MP4
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204.7 MB
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4. Binary Cross-Entropy Loss Function.mp4
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MP4
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90.8 MB
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4. CODE - Stopping Conditions.mp4
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MP4
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72.4 MB
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4. CODE Entropy.mp4
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MP4
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70.1 MB
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4. Code 03 - Assigning Points.mp4
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MP4
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75.6 MB
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4. Concept of Pseudo Residuals.mp4
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MP4
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152.8 MB
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4. Data Loading.mp4
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MP4
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42.8 MB
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4. Data Preparation for ML Model.mp4
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MP4
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83.4 MB
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4. Deep Learning.mp4
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MP4
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54.5 MB
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4. Dominant Color Swatches.mp4
|
MP4
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39.7 MB
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4. Face Detection in Images.mp4
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MP4
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78.7 MB
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4. Finding relations.mp4
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MP4
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67.5 MB
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4. Gradient Descent Updates.mp4
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MP4
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52.8 MB
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4. KNN Algorithm Code.mp4
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MP4
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90.8 MB
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4. Loss Error Function.mp4
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MP4
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195.4 MB
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4. Minimising Distances.mp4
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MP4
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95.3 MB
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4. Naive Bayes Algorithm.mp4
|
MP4
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80.7 MB
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4. Random Forest Algorithm.mp4
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MP4
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118.1 MB
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4. Text Featurization.mp4
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MP4
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44.2 MB
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4. Training & Gradient Updates.mp4
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MP4
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43.3 MB
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4. Wrapper Method.mp4
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MP4
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23 MB
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5. Bernoulli Naive Bayes Example.mp4
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MP4
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138.3 MB
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5. Bias Variance Tradeoff.mp4
|
MP4
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127.4 MB
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5. CODE - Train Child Nodes.mp4
|
MP4
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83.4 MB
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5. Code 01 - Data Prep.mp4
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MP4
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104.3 MB
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5. Code 04 - Updating Centroids.mp4
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MP4
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59.1 MB
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5. Computer Vision.mp4
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MP4
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43.1 MB
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5. Data Preparation.mp4
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MP4
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61.3 MB
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5. Data Preprocessing.mp4
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MP4
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50.3 MB
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5. Eigen Values & Eigen Vectors.mp4
|
MP4
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48.5 MB
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5. Embedded Method.mp4
|
MP4
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12.8 MB
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5. Euclidean and Manhattan Distance.mp4
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MP4
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14.9 MB
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5. Face Detection in Live Video.mp4
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MP4
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49.3 MB
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5. GBDT Algorithm.mp4
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MP4
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245.2 MB
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5. Gradient Update Rule.mp4
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MP4
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146.6 MB
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5. Handling Missing Values.mp4
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MP4
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94.8 MB
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5. Image in K-Colors.mp4
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MP4
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71 MB
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5. Information Gain.mp4
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MP4
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199.5 MB
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5. Model Building.mp4
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MP4
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52.1 MB
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5. Naive Bayes for Text Classification.mp4
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MP4
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160.7 MB
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5. Neural Networks.mp4
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MP4
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58 MB
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5. Training Idea.mp4
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MP4
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48.3 MB
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6. 3 Layer NN.mp4
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MP4
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28 MB
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6. Bias Variance Tradeoff.mp4
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MP4
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83.4 MB
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6. CODE - Explore Decision Tree Model.mp4
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MP4
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102.3 MB
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6. CODE Random Forest.mp4
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MP4
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115.6 MB
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6. CODE Split Data.mp4
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MP4
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135.8 MB
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6. Code 01 - Data Prep.mp4
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MP4
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79.9 MB
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6. Code 02 - Hypothesis.mp4
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MP4
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78.5 MB
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6. Code 05 - Visualizing K-Means & Results.mp4
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MP4
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81.8 MB
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6. Computing Likelihood.mp4
|
MP4
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193.2 MB
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6. Deciding value of K.mp4
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MP4
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6.8 MB
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6. Decision Tree Model Building.mp4
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MP4
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77.8 MB
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6. Face Recognition Project Intro.mp4
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MP4
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15.2 MB
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6. Feature Selection - Code.mp4
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MP4
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63.6 MB
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6. Gradient Descent Optimisation.mp4
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MP4
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110.4 MB
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6. Model Architecture.mp4
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MP4
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33.2 MB
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6. Model Building.mp4
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MP4
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74.6 MB
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6. Model Evaluation.mp4
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MP4
|
67.9 MB
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6. Natural Language Processing.mp4
|
MP4
|
64.4 MB
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6. PCA Summary.mp4
|
MP4
|
18.3 MB
|
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6.1 train.csv
|
CSV
|
119.5 KB
|
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7. Automatic Speech Recognition.mp4
|
MP4
|
100.7 MB
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7. CODE - Gradient Boosting Decision Trees.mp4
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MP4
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131.6 MB
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7. CODE - Prediction.mp4
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MP4
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116.4 MB
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7. CODE Information Gain.mp4
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MP4
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93.8 MB
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7. Code 02 - Hypothesis Logit Model.mp4
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MP4
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34.1 MB
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7. Code 03 - Loss Function.mp4
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MP4
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22.5 MB
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7. Face Recognition 01 - Data Collection.mp4
|
MP4
|
198 MB
|
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7. Gaussian Naive Bayes.mp4
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MP4
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109.3 MB
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7. Gradient Descent Code.mp4
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MP4
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271.3 MB
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7. Hyperparameter tuning.mp4
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MP4
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101.2 MB
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7. KNN and Data Standardisation.mp4
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MP4
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15.2 MB
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7. Softmax Function.mp4
|
MP4
|
18.4 MB
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7. Understanding Eigen Values.mp4
|
MP4
|
44.6 MB
|
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7. Understanding Golf Dataset.mp4
|
MP4
|
218.7 MB
|
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7. Visualize Decision Tree.mp4
|
MP4
|
92.6 MB
|
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7. Why Neural Nets.mp4
|
MP4
|
49.9 MB
|
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7.1 golf.csv
|
CSV
|
409.6 B
|
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8. CODE - Prior Probability.mp4
|
MP4
|
61.1 MB
|
|
|
8. CODE - Variants of Naive Bayes.mp4
|
MP4
|
93.9 MB
|
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|
8. Code 03 - Binary Cross Entropy Loss.mp4
|
MP4
|
19.4 MB
|
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|
8. Code 04 - Gradient Computation.mp4
|
MP4
|
222.3 MB
|
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8. Construction of Decision Trees.mp4
|
MP4
|
66.4 MB
|
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8. Face Recognition 02 - Loading Data.mp4
|
MP4
|
71.7 MB
|
|
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8. Gradient Descent - for Linear Regression.mp4
|
MP4
|
51.8 MB
|
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|
8. Handling Numeric Features.mp4
|
MP4
|
110 MB
|
|
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8. KNN Pros and Cons.mp4
|
MP4
|
53.8 MB
|
|
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8. Model Training.mp4
|
MP4
|
17.3 MB
|
|
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8. PCA Code.mp4
|
MP4
|
50.6 MB
|
|
|
8. Reinforcement Learning.mp4
|
MP4
|
43.9 MB
|
|
|
8. Tensorflow Playground.mp4
|
MP4
|
88.7 MB
|
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8. XGBoost.mp4
|
MP4
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119.3 MB
|
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9. Adaptive Boosting (AdaBoost).mp4
|
MP4
|
118.9 MB
|
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9. Bias Variance Tradeoff.mp4
|
MP4
|
58.9 MB
|
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|
9. CODE - Conditional Probability.mp4
|
MP4
|
108.1 MB
|
|
|
9. CODE -Data Preparation.mp4
|
MP4
|
43.8 MB
|
|
|
9. Choosing the right dimensions.mp4
|
MP4
|
45.4 MB
|
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|
9. Code 04 - Gradient Computation.mp4
|
MP4
|
45.2 MB
|
|
|
9. Code 05 - Training Loop.mp4
|
MP4
|
86.7 MB
|
|
|
9. Face Recognition 03 - Predictions using KNN.mp4
|
MP4
|
99.6 MB
|
|
|
9. KNN using Sk-Learn.html
|
HTML
|
409.6 B
|
|
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9. Model evaluation.mp4
|
MP4
|
50.2 MB
|
|
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9. Pre-requisites.html
|
HTML
|
921.6 B
|
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9. Stopping Conditions.mp4
|
MP4
|
98.3 MB
|
|
|
9. The Math of Training.mp4
|
MP4
|
105.3 MB
|
|
|
[CourseClub.Me].url
|
URL
|
102.4 B
|
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[FreeCourseSite.com].url
|
URL
|
102.4 B
|
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[GigaCourse.Com].url
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URL
|
0 B
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