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[TutsNode.com] - K-Means for Cluster Analysis and Unsupervised Learning in R/4. Unsupervised learning K-Means in R Theory & Practise/5. K-means clustering Application to email marketing.mp4 116.0 MB
[TutsNode.com] - K-Means for Cluster Analysis and Unsupervised Learning in R/5. Advanced K-Means Clustering Analysis/1. Starting with Fuzzy K-means in R.mp4 107.1 MB
[TutsNode.com] - K-Means for Cluster Analysis and Unsupervised Learning in R/7. Your Independent Project in K-Means CLuster Analysis/2. Project Assignment.mp4 71.6 MB
[TutsNode.com] - K-Means for Cluster Analysis and Unsupervised Learning in R/5. Advanced K-Means Clustering Analysis/2. Entropy Weighted K-Means in R.mp4 64.9 MB
[TutsNode.com] - K-Means for Cluster Analysis and Unsupervised Learning in R/5. Advanced K-Means Clustering Analysis/3. Selecting the number of clusters for unsupervised Clustering methods (K-Means).mp4 62.2 MB
[TutsNode.com] - K-Means for Cluster Analysis and Unsupervised Learning in R/7. Your Independent Project in K-Means CLuster Analysis/1. Introduction to Your Project based on a case study.mp4 60.9 MB
[TutsNode.com] - K-Means for Cluster Analysis and Unsupervised Learning in R/3. R Crash Course - get started with R-programming in R-Studio/4. Lab data types and data structures in R.mp4 50.4 MB
[TutsNode.com] - K-Means for Cluster Analysis and Unsupervised Learning in R/2. Software used in this course/3. Lab Get started with R in RStudio.mp4 50.0 MB
[TutsNode.com] - K-Means for Cluster Analysis and Unsupervised Learning in R/1. Introduction/2. What is Machine Leraning and it's main types.mp4 49.1 MB
[TutsNode.com] - K-Means for Cluster Analysis and Unsupervised Learning in R/6. Performance Evaluation of Unsupervised Learning CLustering Algorithms in R/1. How to assess a Clustering Tendency of the dataset.mp4 44.4 MB
[TutsNode.com] - K-Means for Cluster Analysis and Unsupervised Learning in R/2. Software used in this course/2. How to install R and RStudio in 2020.mp4 40.6 MB
[TutsNode.com] - K-Means for Cluster Analysis and Unsupervised Learning in R/6. Performance Evaluation of Unsupervised Learning CLustering Algorithms in R/2. Assessing the performance of unsupervised learning (clustering) algorithms.mp4 40.3 MB
[TutsNode.com] - K-Means for Cluster Analysis and Unsupervised Learning in R/3. R Crash Course - get started with R-programming in R-Studio/5. Vectors' operations in R.mp4 37.7 MB
[TutsNode.com] - K-Means for Cluster Analysis and Unsupervised Learning in R/3. R Crash Course - get started with R-programming in R-Studio/8. Functions in R - overview.mp4 33.8 MB
[TutsNode.com] - K-Means for Cluster Analysis and Unsupervised Learning in R/7. Your Independent Project in K-Means CLuster Analysis/1.1 samsungData.rda 28.6 MB
[TutsNode.com] - K-Means for Cluster Analysis and Unsupervised Learning in R/3. R Crash Course - get started with R-programming in R-Studio/3. Overview of data types and data structures in R.mp4 28.5 MB
[TutsNode.com] - K-Means for Cluster Analysis and Unsupervised Learning in R/6. Performance Evaluation of Unsupervised Learning CLustering Algorithms in R/3. How to compare the performance of different unsupervised clustering algoritms.mp4 28.5 MB
[TutsNode.com] - K-Means for Cluster Analysis and Unsupervised Learning in R/3. R Crash Course - get started with R-programming in R-Studio/9. Lab For Loops in R.mp4 26.0 MB
[TutsNode.com] - K-Means for Cluster Analysis and Unsupervised Learning in R/4. Unsupervised learning K-Means in R Theory & Practise/6. Heatmaps to visualize K-Means Results in R Examplery Lab.mp4 25.9 MB
[TutsNode.com] - K-Means for Cluster Analysis and Unsupervised Learning in R/3. R Crash Course - get started with R-programming in R-Studio/1. Lab Installing Packages and Package Management in R.mp4 25.3 MB

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12. Appendix/3. Windows-Focused Environment Setup 2018.mp4 195.4 MB
9. Applications to Recommender Systems/9. Recommender RBM Code pt 3.mp4 134.8 MB
9. Applications to Recommender Systems/5. AutoRec in Code.mp4 107.3 MB
10. Basics Review/4. (Review) Tensorflow Neural Network in Code.mp4 102.1 MB
10. Basics Review/1. (Review) Theano Basics.mp4 98.0 MB
10. Basics Review/2. (Review) Theano Neural Network in Code.mp4 91.3 MB
9. Applications to Recommender Systems/10. Recommender RBM Code Speedup.vtt 87.0 MB
9. Applications to Recommender Systems/10. Recommender RBM Code Speedup.mp4 87.0 MB
10. Basics Review/3. (Review) Tensorflow Basics.mp4 85.4 MB
12. Appendix/9. Proof that using Jupyter Notebook is the same as not using it.vtt 82.1 MB
12. Appendix/9. Proof that using Jupyter Notebook is the same as not using it.mp4 82.1 MB
9. Applications to Recommender Systems/7. Recommender RBM Code pt 1.mp4 73.8 MB
9. Applications to Recommender Systems/1. Recommender Systems Section Introduction.mp4 71.5 MB
10. Basics Review/6. (Review) Keras in Code pt 1.mp4 69.4 MB
2. Principal Components Analysis/9. PCA Application Naive Bayes.mp4 56.3 MB
2. Principal Components Analysis/3. Why does PCA work (PCA derivation).mp4 53.8 MB
2. Principal Components Analysis/2. How does PCA work.mp4 53.4 MB
5. Restricted Boltzmann Machines/6. Training an RBM (part 1).mp4 51.5 MB
9. Applications to Recommender Systems/4. AutoRec.mp4 51.3 MB
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10. Appendix/2. Windows-Focused Environment Setup 2018.mp4 195.4 MB
10. Appendix/8. Proof that using Jupyter Notebook is the same as not using it.mp4 82.1 MB
4. Hidden Markov Models for Discrete Observations/11. Discrete HMM in Code.mp4 49.7 MB
6. HMMs for Continuous Observations/3. Continuous-Observation HMM in Code (part 1).mp4 49.0 MB
6. HMMs for Continuous Observations/5. Continuous HMM in Theano.mp4 47.6 MB
10. Appendix/3. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp4 46.0 MB
10. Appendix/7. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.mp4 40.9 MB
10. Appendix/11. What order should I take your courses in (part 2).mp4 39.5 MB
5. Discrete HMMs Using Deep Learning Libraries/3. Discrete HMM in Theano.mp4 32.2 MB
10. Appendix/10. What order should I take your courses in (part 1).mp4 30.8 MB
4. Hidden Markov Models for Discrete Observations/13. Discrete HMM Updates in Code with Scaling.mp4 30.6 MB
3. Markov Models Example Problems and Applications/4. Example Application Build a 2nd-order language model and generate phrases.mp4 28.2 MB
5. Discrete HMMs Using Deep Learning Libraries/4. Improving our Gradient Descent-Based HMM.mp4 27.2 MB
10. Appendix/4. How to Code by Yourself (part 1).mp4 25.7 MB
7. HMMs for Classification/2. HMM Classification on Poetry Data (Robert Frost vs. Edgar Allan Poe).mp4 25.6 MB
5. Discrete HMMs Using Deep Learning Libraries/2. Theano Scan Tutorial.mp4 24.9 MB
5. Discrete HMMs Using Deep Learning Libraries/5. Tensorflow Scan Tutorial.mp4 24.2 MB
5. Discrete HMMs Using Deep Learning Libraries/1. Gradient Descent Tutorial.mp4 23.9 MB
6. HMMs for Continuous Observations/6. Continuous HMM in Tensorflow.mp4 23.6 MB
4. Hidden Markov Models for Discrete Observations/4. The Forward-Backward Algorithm.mp4 23.5 MB

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00003 Exploratory_Data_Analysis.mp4 83.8 MB
00010 Extreme_Learning_Machine.mp4 51.9 MB
00011 The_SuperEnsemble.mp4 48.5 MB
00013 Simulated_Annealing.mp4 48.3 MB
00017 MLP_versus_DLVQ_versus_Jordan_versus_Elman.mp4 47.1 MB
00012 Genetic_Algorithms.mp4 45.3 MB
00016 Keras_and_TensorFlow.mp4 43.6 MB
00004 Outlier_Detection.mp4 40.5 MB
00009 Stacking.mp4 33.2 MB
00002 Mesos_Initial_Setup.mp4 32.2 MB
00005 Sample_Selection_and_Dimensionality_Reduction.mp4 31.1 MB
00015 Self-Control_and_Self-Training.mp4 29.9 MB
00019 Prioritizing_Attention.mp4 29.4 MB
00008 Continuous_Prediction.mp4 28.9 MB
00006 Creating_Training_and_Testing_a_model_of_Neural_Networks.mp4 28.2 MB
00018 Error_Correction_and_Boltzmann_Rule.mp4 27.2 MB
00014 Grafana_with_Webhook.mp4 18.4 MB
00007 Bayesian_Hyper-Parameterization.mp4 18.1 MB
00001 The_Course_Overview.mp4 2.1 MB
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12. Appendix/3. Windows-Focused Environment Setup 2018.mp4 195.4 MB
9. Applications to Recommender Systems/9. Recommender RBM Code pt 3.mp4 134.8 MB
9. Applications to Recommender Systems/5. AutoRec in Code.mp4 107.3 MB
10. Basics Review/4. (Review) Tensorflow Neural Network in Code.mp4 102.1 MB
10. Basics Review/1. (Review) Theano Basics.mp4 98.0 MB
10. Basics Review/2. (Review) Theano Neural Network in Code.mp4 91.3 MB
9. Applications to Recommender Systems/10. Recommender RBM Code Speedup.vtt 87.0 MB
9. Applications to Recommender Systems/10. Recommender RBM Code Speedup.mp4 87.0 MB
10. Basics Review/3. (Review) Tensorflow Basics.mp4 85.4 MB
12. Appendix/9. Proof that using Jupyter Notebook is the same as not using it.vtt 82.1 MB
12. Appendix/9. Proof that using Jupyter Notebook is the same as not using it.mp4 82.1 MB
9. Applications to Recommender Systems/7. Recommender RBM Code pt 1.mp4 73.8 MB
9. Applications to Recommender Systems/1. Recommender Systems Section Introduction.mp4 71.5 MB
10. Basics Review/6. (Review) Keras in Code pt 1.mp4 69.4 MB
2. Principal Components Analysis/9. PCA Application Naive Bayes.mp4 56.3 MB
2. Principal Components Analysis/3. Why does PCA work (PCA derivation).mp4 53.8 MB
2. Principal Components Analysis/2. How does PCA work.mp4 53.4 MB
5. Restricted Boltzmann Machines/6. Training an RBM (part 1).mp4 51.5 MB
9. Applications to Recommender Systems/4. AutoRec.mp4 51.3 MB
5. Restricted Boltzmann Machines/10. RBM in Code (Theano) with Greedy Layer-Wise Training on MNIST.mp4 50.1 MB

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10. Setting Up Your Environment/1. Windows-Focused Environment Setup 2018.mp4 195.4 MB
11. Extra Help With Python Coding for Beginners/3. Proof that using Jupyter Notebook is the same as not using it.mp4 82.1 MB
4. Hidden Markov Models for Discrete Observations/5. The Forward-Backward Algorithm (part 1).mp4 68.3 MB
4. Hidden Markov Models for Discrete Observations/12. HMM Training (part 3).mp4 63.1 MB
4. Hidden Markov Models for Discrete Observations/9. The Viterbi Algorithm (part 2).mp4 62.2 MB
4. Hidden Markov Models for Discrete Observations/13. HMM Training (part 4).mp4 58.3 MB
4. Hidden Markov Models for Discrete Observations/16. Discrete HMM in Code.mp4 49.7 MB
6. HMMs for Continuous Observations/3. Continuous-Observation HMM in Code (part 1).mp4 49.0 MB
6. HMMs for Continuous Observations/5. Continuous HMM in Theano.mp4 47.6 MB
10. Setting Up Your Environment/2. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp4 46.1 MB
4. Hidden Markov Models for Discrete Observations/2. HMM - Basic Examples.mp4 44.4 MB
4. Hidden Markov Models for Discrete Observations/11. HMM Training (part 2).mp4 41.9 MB
12/2. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.mp4 40.9 MB
13. Appendix FAQ/2. BONUS Where to get Udemy coupons and FREE deep learning material.mp4 39.7 MB
12/4. What order should I take your courses in (part 2).mp4 39.5 MB
4. Hidden Markov Models for Discrete Observations/14. How to Choose the Number of Hidden States.mp4 35.5 MB
2. Markov Models/2. Markov Models.mp4 34.1 MB
4. Hidden Markov Models for Discrete Observations/3. Parameters of an HMM.mp4 32.8 MB
5. Discrete HMMs Using Deep Learning Libraries/3. Discrete HMM in Theano.mp4 32.2 MB
12/3. What order should I take your courses in (part 1).mp4 30.8 MB

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[TutsNode.com] - Unsupervised Machine Learning Hidden Markov Models in Python/10. Setting Up Your Environment (FAQ by Student Request)/1. Windows-Focused Environment Setup 2018.mp4 195.4 MB
[TutsNode.com] - Unsupervised Machine Learning Hidden Markov Models in Python/11. Extra Help With Python Coding for Beginners (FAQ by Student Request)/3. Proof that using Jupyter Notebook is the same as not using it.mp4 82.1 MB
[TutsNode.com] - Unsupervised Machine Learning Hidden Markov Models in Python/1. Introduction and Outline/4. Anyone Can Succeed in this Course.mp4 81.7 MB
[TutsNode.com] - Unsupervised Machine Learning Hidden Markov Models in Python/4. Hidden Markov Models for Discrete Observations/5. The Forward-Backward Algorithm (part 1).mp4 68.3 MB
[TutsNode.com] - Unsupervised Machine Learning Hidden Markov Models in Python/4. Hidden Markov Models for Discrete Observations/12. HMM Training (part 3).mp4 63.1 MB
[TutsNode.com] - Unsupervised Machine Learning Hidden Markov Models in Python/4. Hidden Markov Models for Discrete Observations/9. The Viterbi Algorithm (part 2).mp4 62.2 MB
[TutsNode.com] - Unsupervised Machine Learning Hidden Markov Models in Python/4. Hidden Markov Models for Discrete Observations/13. HMM Training (part 4).mp4 58.3 MB
[TutsNode.com] - Unsupervised Machine Learning Hidden Markov Models in Python/4. Hidden Markov Models for Discrete Observations/16. Discrete HMM in Code.mp4 49.7 MB
[TutsNode.com] - Unsupervised Machine Learning Hidden Markov Models in Python/6. HMMs for Continuous Observations/3. Continuous-Observation HMM in Code (part 1).mp4 49.0 MB
[TutsNode.com] - Unsupervised Machine Learning Hidden Markov Models in Python/6. HMMs for Continuous Observations/5. Continuous HMM in Theano.mp4 47.6 MB
[TutsNode.com] - Unsupervised Machine Learning Hidden Markov Models in Python/10. Setting Up Your Environment (FAQ by Student Request)/2. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp4 46.0 MB
[TutsNode.com] - Unsupervised Machine Learning Hidden Markov Models in Python/4. Hidden Markov Models for Discrete Observations/2. HMM - Basic Examples.mp4 44.4 MB
[TutsNode.com] - Unsupervised Machine Learning Hidden Markov Models in Python/4. Hidden Markov Models for Discrete Observations/11. HMM Training (part 2).mp4 41.9 MB
[TutsNode.com] - Unsupervised Machine Learning Hidden Markov Models in Python/12. Effective Learning Strategies for Machine Learning (FAQ by Student Request)/2. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.mp4 40.8 MB
[TutsNode.com] - Unsupervised Machine Learning Hidden Markov Models in Python/13. Appendix FAQ Finale/2. BONUS Where to get Udemy coupons and FREE deep learning material.mp4 39.7 MB
[TutsNode.com] - Unsupervised Machine Learning Hidden Markov Models in Python/12. Effective Learning Strategies for Machine Learning (FAQ by Student Request)/4. Machine Learning and AI Prerequisite Roadmap (pt 2).mp4 39.4 MB
[TutsNode.com] - Unsupervised Machine Learning Hidden Markov Models in Python/4. Hidden Markov Models for Discrete Observations/14. How to Choose the Number of Hidden States.mp4 35.5 MB
[TutsNode.com] - Unsupervised Machine Learning Hidden Markov Models in Python/2. Markov Models/2. Markov Models.mp4 34.0 MB
[TutsNode.com] - Unsupervised Machine Learning Hidden Markov Models in Python/4. Hidden Markov Models for Discrete Observations/3. Parameters of an HMM.mp4 32.8 MB
[TutsNode.com] - Unsupervised Machine Learning Hidden Markov Models in Python/5. Discrete HMMs Using Deep Learning Libraries/3. Discrete HMM in Theano.mp4 32.2 MB

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5. Appendix/2. Windows-Focused Environment Setup 2018.mp4 195.4 MB
5. Appendix/8. Proof that using Jupyter Notebook is the same as not using it.vtt 82.1 MB
5. Appendix/8. Proof that using Jupyter Notebook is the same as not using it.mp4 82.1 MB
5. Appendix/3. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp4 46.1 MB
5. Appendix/7. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.mp4 40.8 MB
5. Appendix/11. What order should I take your courses in (part 2).mp4 39.5 MB
3. Hierarchical Clustering/5. Application Donald Trump vs. Hillary Clinton Tweets.mp4 37.0 MB
2. K-Means Clustering/5. Soft K-Means in Python Code.mp4 31.7 MB
4. Gaussian Mixture Models (GMMs)/3. Write a Gaussian Mixture Model in Python Code.mp4 31.6 MB
5. Appendix/10. What order should I take your courses in (part 1).mp4 30.8 MB
3. Hierarchical Clustering/4. Application Evolution.mp4 27.7 MB
2. K-Means Clustering/12. K-Means Application Finding Clusters of Related Words.mp4 27.2 MB
2. K-Means Clustering/3. Soft K-Means.mp4 26.5 MB
5. Appendix/4. How to Code by Yourself (part 1).mp4 25.7 MB
5. Appendix/6. How to Succeed in this Course (Long Version).mp4 19.2 MB
2. K-Means Clustering/7. Examples of where K-Means can fail.mp4 17.8 MB
5. Appendix/5. How to Code by Yourself (part 2).mp4 15.5 MB
2. K-Means Clustering/1. An Easy Introduction to K-Means Clustering.mp4 13.2 MB
3. Hierarchical Clustering/3. Using Hierarchical Clustering in Python and Interpreting the Dendrogram.mp4 12.4 MB
2. K-Means Clustering/9. How to Evaluate a Clustering (Purity, Davies-Bouldin Index).mp4 11.9 MB

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