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Victoriya Fevari - Getting Naked and Using My Dildo! 1080.mp4  640.58 MB

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5.Creating Forms Over Data Pages/0515 Using the Repeater, Alternate Layout, and Carousel.mp4  52.07 MB
3.Creating Horizontal Navigation for Your Application/0302 Building Our First Horizontal Navigation.mp4  51.51 MB
5.Creating Forms Over Data Pages/0509 Demo of Code for Input Form.mp4  51.17 MB
6.Standard Business Forms/0615 Address Screen Sample.mp4  43.33 MB
5.Creating Forms Over Data Pages/0505 DetailView Demo.mp4  42.77 MB

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03.Building a Clustering Model with Spark/0302.Implementing GMM in Apache Spark.mp4  31.52 MB
04.Dimensionality Reductions and Recommendation Engines/0403.Using Recommendation Engine to Get Top Recommendations.mp4  26.32 MB
01.Advanced Text Processing in Spark and Building a Classification Model/0104.Extracting Features from Data – Transforming Text into Vector of Numbers.mp4  22.71 MB
01.Advanced Text Processing in Spark and Building a Classification Model/0101.The Course Overview.mp4  19.2 MB
01.Advanced Text Processing in Spark and Building a Classification Model/0102.Analyzing Text Input Data.mp4  18.88 MB

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video/4 - Clustering Recommendations and Probability.mp4  484.86 MB
video/3 - Classifying Web Documents_ The Code.mp4  429.7 MB
video/2 - Classifying Web Documents_ The Theory.mp4  263.32 MB
video/1 - Introduction.mp4  182.93 MB
video/5 - Conclusion.mp4  103.09 MB

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08 Apache Spark_ Machine Learning on Big Data/061 [Activity] Decision Trees in Spark.mp4  88.24 MB
08 Apache Spark_ Machine Learning on Big Data/057 [Activity] Installing Spark - Part 2.mp4  85.81 MB
06 More Data Mining and Machine Learning Techniques/048 Reinforcement Learning.mp4  63.56 MB
05 Recommender Systems/041 [Activity] Making Movie Recommendations to People.mp4  63.25 MB
08 Apache Spark_ Machine Learning on Big Data/062 [Activity] K-Means Clustering in Spark.mp4  62.85 MB

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1 - Introducing XGBoost.mp4  116.09 MB
7 - XGBoost Prediction in Python.mp4  54.76 MB
5 - XGBoost Parameter Tuning in Python.mp4  34.3 MB
4 - XGBoost Model Implementation in Python.mp4  33.05 MB
6 - XGBoost Model Evaluation Method in Python.mp4  31.57 MB

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4. Introduction to Optimisation and the Gradient Descent Algorithm/8. [Python] - Advanced Functions and the Pitfalls of Optimisation (Part 1).mp4  291.33 MB
4. Introduction to Optimisation and the Gradient Descent Algorithm/6. [Python] - Loops and the Gradient Descent Algorithm.mp4  287.45 MB
10. Build an Artificial Neural Network to Recognise Images using Keras & Tensorflow/12. Model Evaluation and the Confusion Matrix.mp4  251.83 MB
5. Predict House Prices with Multivariable Linear Regression/32. Build a Valuation Tool (Part 3) Docstrings & Creating your own Python Module.mp4  244.16 MB
4. Introduction to Optimisation and the Gradient Descent Algorithm/10. Understanding the Learning Rate.mp4  236.6 MB

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5. Data Science Environment Setup/8. Windows Environment Setup 2.mp4  227.6 MB
9. Scikit-learn Creating Machine Learning Models/7. Typical scikit-learn Workflow.mp4  190.19 MB
9. Scikit-learn Creating Machine Learning Models/8. Optional Debugging Warnings In Jupyter.mp4  176.13 MB
16. Career Advice + Extra Bits/9. CWD Git + Github.mp4  176.11 MB
9. Scikit-learn Creating Machine Learning Models/39. Tuning Hyperparameters.mp4  175.56 MB

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16 DataBricks and Spark/078 Zeppelin Notebooks on AWS Elastic MapReduce.mp4  67.19 MB
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13 Model Evaluation/063 Spark Model Evaluation - Documentation Example.mp4  64.21 MB
16 DataBricks and Spark/075 Databricks Overview.mp4  62.44 MB
13 Model Evaluation/064 Spark - Model Evaluation - Regression Example.mp4  61.81 MB

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Part 02-Module 04-Lesson 02_Deep Q-Learning/07. Experience Replay-wX_-SZG-YMQ.mp4  48.38 MB
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Part 01-Module 11-Lesson 04_Gaussian Mixture Models and Cluster Validation/19. MLND - Unsupervised Learning - L3 20 Internal Validation Indices MAIN V1 V2-39JruOTptKI.mp4  40.74 MB
Part 02-Module 04-Lesson 02_Deep Q-Learning/10. DQN Improvements-Zfdbp93A2GU.mp4  39.4 MB
Part 02-Module 03-Lesson 05_Monte Carlo Methods/03. MC Prediction State Values-0q2wSWyuBj8.mp4  33.39 MB

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17. Logistic Regression/4. Case Study.mp4  198.2 MB
7. Data Visualisation/2. Seaborn.mp4  184.74 MB
15. Model Selection Part1/4. Gridsearch Case study Part2.mp4  178.88 MB
7. Data Visualisation/1. Matplotlib.mp4  172.76 MB
2. Numpy/3. Numpy Operations Part2.mp4  169.97 MB

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08 Introduction to Deep Learning [Optional]/056 [Activity] Handwriting Recognition with Tensorflow part 1.mp4  181.85 MB
08 Introduction to Deep Learning [Optional]/052 [Activity] Playing with Tensorflow.mp4  145.4 MB
09 Deep Learning for Recommender Systems/070 [Activity] Recommendations with RBMs part 1.mp4  144.44 MB
08 Introduction to Deep Learning [Optional]/067 [Activity] Sentiment Analysis of Movie Reviews using RNNs and Keras.mp4  119.78 MB
10 Scaling it Up/087 DSSTNE in Action.mp4  116.66 MB

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12 Logistic Regression/096 Logistic Regression in R - Step 5.mp4  93.76 MB
31 Artificial Neural Networks/225 ANN in Python - Step 2.mp4  84.87 MB
17 Decision Tree Classification/123 Decision Tree Classification in R.mp4  68.18 MB
14 Support Vector Machine (SVM)/105 SVM in R.mp4  65.31 MB
18 Random Forest Classification/127 Random Forest Classification in R.mp4  64.11 MB

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24 - Perform Metric Selection on Real Data.mp4  220.23 MB
02 - Using Feature Scaling to Standardize Data.mp4  37.45 MB
08 - Implementing kNN on the Data Set.mp4  34.24 MB
13 - Gradient Boosting Trees and Bayes Optimization.mp4  33.36 MB
16 - Implement Stacking.mp4  31.2 MB

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5. Data Science Environment Setup/8. Windows Environment Setup 2.mp4  227.6 MB
9. Scikit-learn Creating Machine Learning Models/7. Typical scikit-learn Workflow.mp4  190.18 MB
9. Scikit-learn Creating Machine Learning Models/8. Optional Debugging Warnings In Jupyter.mp4  176.13 MB
16. Career Advice + Extra Bits/9. CWD Git + Github.mp4  176.12 MB
9. Scikit-learn Creating Machine Learning Models/38. Tuning Hyperparameters.mp4  175.53 MB

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6. Appendix/3. Windows-Focused Environment Setup 2018.mp4  186.29 MB
6. Appendix/9. Proof that using Jupyter Notebook is the same as not using it.mp4  78.26 MB
3. Bootstrap Estimates and Bagging/1. Bootstrap Estimation.mp4  47.72 MB
6. Appendix/4. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp4  43.92 MB
2. Bias-Variance Trade-Off/4. Polynomial Regression Demo.mp4  41.75 MB

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05.Build Advanced Trading Algorithm/0502.Implement Scalpers Trading Strategy.mp4  121.94 MB
Exercise Files/exercise_files.zip  90.05 MB
01.Building Your First Trading Bot/0105.Fetching and Understanding the Dataset.mp4  68.3 MB
03.Build a Trading Algorithm/0303.Implement Exploit Correlation Strategy.mp4  57.85 MB
02.Design a Machine Learning Model/0202.Build and Implement Random Forests Algorithm.mp4  51.78 MB

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004.Search for New Physics in Rare Decays/013. Lepton Flavour Violation.mp4  53.88 MB
001.Introduction/002. Experimental particle physics.mp4  52.59 MB
001.Introduction/003. Testing hypotheses experimentally.mp4  49.03 MB
001.Introduction/001. Introduction into the course.mp4  48.31 MB
005.Search for Dark Matter Hints with Machine Learning at new CERN experiment/017. Search for Dark Matter at Accelerator Experiment.mp4  47.09 MB

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