- 【影视】 O'Reilly - Building Data Pipelines with Python
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1. Welcome To The Course.mp4 9.5 MB
10. Celery Architecture & Set Up.mp4 38.2 MB
11. Writing Your First Tasks.mp4 37.9 MB
12. Deploying Your Tasks.mp4 36.0 MB
13. Scaling Your Workers.mp4 53.2 MB
14. Monitoring With Flower.mp4 27.2 MB
15. Advanced Celery Features.mp4 36.9 MB
16. Why Dask.mp4 17.0 MB
17. First Steps With Dask.mp4 41.6 MB
18. Dask Bags.mp4 56.1 MB
19. Dask Distributed.mp4 54.5 MB
2. About The Author.mp4 11.5 MB
20. What Are Data Pipelines.mp4 14.1 MB
21. Luigi And Airflow A Comparison.mp4 23.7 MB
22. First Steps With Luigi.mp4 41.2 MB
23. More Complex Luigi Tasks.mp4 43.9 MB
24. Introduction To Hadoop.mp4 45.1 MB
25. First Steps With Airflow.mp4 44.2 MB
26. Custom Tasks With Airflow.mp4 52.3 MB
27. Advanced Airflow Subdags And Branches.mp4 63.7 MB
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13 Make Web Applications In Python Using Django/attached_files/156 Django tutorial 22 Navigation Bar Touchup/HTML-files-used-for-the-project.txt 5.6 kB
02 Basic Python Concepts/quizzes/001 Quiz For Section 1.html 4.2 kB
03 Control Structures In Python/quizzes/002 Quiz For Section 2.html 4.3 kB
04 Functions Modules In Python/quizzes/003 Quiz For Section 3.html 3.1 kB
05 Exception Handling File Handling In Python/quizzes/004 Quiz For Section 4.html 3.6 kB
06 Some More Types In Python/quizzes/005 Quiz For Section 5.html 2.5 kB
01 Introduction/001 Introduction To The Course.mp4 5.0 MB
02 Basic Python Concepts/002 Installing Python And PyCharm.mp4 21.7 MB
02 Basic Python Concepts/003 Hello World Program In Python.mp4 19.2 MB
02 Basic Python Concepts/004 Some other mathematical operations in Python.mp4 12.7 MB
02 Basic Python Concepts/005 Strings In Python.mp4 11.1 MB
02 Basic Python Concepts/006 Accepting input from the user in Python.mp4 11.0 MB
02 Basic Python Concepts/007 Performing operations on a string in Python.mp4 11.4 MB
02 Basic Python Concepts/008 Variables in Python.mp4 14.3 MB
02 Basic Python Concepts/009 In place operators in Python..mp4 13.3 MB
02 Basic Python Concepts/010 Writing our very first program in PyCharm.mp4 10.8 MB
02 Basic Python Concepts/011 Coding Challenge Part 1.mp4 15.1 MB
02 Basic Python Concepts/012 Notes Summary For Section 1.html 4.7 kB
03 Control Structures In Python/013 If statement in Python.mp4 17.1 MB
03 Control Structures In Python/014 Elif statement in Python.mp4 11.6 MB
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01 - Exercise 0 - The Setup (Linux).mp4 1.1 GB
47 - Exercise 42 - Is-A, Has-A, Objects, and Classes.mp4 145.2 MB
35 - Exercise 30 - Else and If.mp4 78.9 MB
36 - Exercise 31 - Making Decisions.mp4 178.7 MB
37 - Exercise 32 - Loops and Lists.mp4 274.6 MB
38 - Exercise 33 - While Loops.mp4 219.2 MB
39 - Exercise 34 - Accessing Elements of Lists.mp4 164.1 MB
40 - Exercise 35 - Branches and Functions.mp4 141.5 MB
41 - Exercise 36 - Designing and Debugging.mp4 164.2 MB
42 - Exercise 37 - Symbol Review.mp4 225.7 MB
43 - Exercise 38 - Doing Things to Lists.mp4 299.7 MB
44 - Exercise 39 - Dictionaries, Oh Lovely Dictionaries.mp4 219.9 MB
45 - Exercise 40 - Modules, Classes, and Objects.mp4 424.0 MB
46 - Exercise 41 - Learning to Speak Object-Oriented.mp4 361.2 MB
48 - Exercise 43 - Basic Object-Oriented Analysis and Design.mp4 432.1 MB
02 - Exercise 0 - The Setup (macOS).mp4 238.9 MB
49 - Exercise 44 - Inheritance Versus Composition.mp4 176.2 MB
50 - Exercise 45 - You Make a Game.mp4 160.7 MB
51 - Exercise 46 - A Project Skeleton (macOS).mp4 417.4 MB
52 - Exercise 46 - A Project Skeleton (Windows).mp4 490.4 MB
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01. Introduction To Object Oriented Python/0101 Introduction And About The Author.mp4 10.0 MB
01. Introduction To Object Oriented Python/0102 What Is Object Oriented Programming And Why.mp4 13.7 MB
01. Introduction To Object Oriented Python/0103 Object-Oriented Python.mp4 26.0 MB
01. Introduction To Object Oriented Python/0104 Modules Versus Classes.mp4 16.4 MB
02. Getting Started/0201 Prerequisites And Toolkit.mp4 8.2 MB
02. Getting Started/0202 Choosing An IDE Or Text Editor And Workflow.mp4 10.8 MB
03. Classes/0301 Classes, Instances, Attributes And Methods.mp4 25.2 MB
03. Classes/0302 Defining A Class.mp4 22.8 MB
03. Classes/0303 Instance Methods.mp4 27.1 MB
03. Classes/0304 Instance Attributes.mp4 15.3 MB
03. Classes/0305 Encapsulation.mp4 27.0 MB
03. Classes/0306 Init Constructor.mp4 27.4 MB
03. Classes/0307 Class Attributes.mp4 12.6 MB
03. Classes/0308 Working With Class And Instance Data.mp4 30.1 MB
03. Classes/0309 Assignment 1.mp4 18.2 MB
03. Classes/0310 Assignment 1 - Solution.mp4 18.9 MB
04. Inheritance And Polymorphism/0401 Inheriting Attributes.mp4 18.5 MB
04. Inheritance And Polymorphism/0402 Inheritance Examples.mp4 31.2 MB
04. Inheritance And Polymorphism/0403 Polymorphism.mp4 30.5 MB
04. Inheritance And Polymorphism/0404 Inheriting The Constructor.mp4 12.8 MB
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01 Course Introduction/attached_files/004 Course FAQ/Python-for-Finance-Repo.zip 10.7 MB
02 Course Materials and Set-up/attached_files/006 Course Installation Guide/Python-for-Finance-Repo.zip 10.7 MB
01 Course Introduction/001 Introduction to Course.mp4 8.9 MB
01 Course Introduction/002 Course Overview Lecture DONT SKIP THIS.mp4 9.0 MB
01 Course Introduction/003 Did you skip the last lecture Please go back and view it.html 1.0 kB
01 Course Introduction/004 Course FAQ.html 2.1 kB
02 Course Materials and Set-up/005 Course Installation Help Notes.html 1.5 kB
02 Course Materials and Set-up/006 Course Installation Guide.mp4 21.7 MB
03 Python Crash Course/007 Welcome to the Python Crash Course.mp4 2.4 MB
03 Python Crash Course/008 Introduction to Crash Course.mp4 2.5 MB
03 Python Crash Course/009 Python Crash Course Part One.mp4 39.8 MB
03 Python Crash Course/010 Python Crash Course Part Two.mp4 25.4 MB
03 Python Crash Course/011 Python Crash Course Part Three.mp4 30.0 MB
03 Python Crash Course/012 Python Crash Course Exercises.mp4 13.1 MB
03 Python Crash Course/013 Python Crash Course Exercise Solutions.mp4 23.2 MB
04 NumPy/014 Welcome to NumPy.mp4 3.0 MB
04 NumPy/015 Introduction to NumPy.mp4 3.3 MB
04 NumPy/016 NumPy Arrays.mp4 33.5 MB
04 NumPy/017 Numpy Operations.mp4 10.0 MB
04 NumPy/018 Numpy Indexing.mp4 21.3 MB
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01 Introduction and Logistics/001 Introduction and Outline.mp4 16.6 MB
01 Introduction and Logistics/002 Where to get the Code.mp4 5.4 MB
01 Introduction and Logistics/003 How to Succeed in this Course.mp4 15.1 MB
02 Background Review/004 Review Intro.mp4 4.4 MB
02 Background Review/005 Review of Markov Decision Processes.mp4 12.8 MB
02 Background Review/006 Review of Dynamic Programming.mp4 6.8 MB
02 Background Review/007 Review of Monte Carlo Methods.mp4 6.5 MB
02 Background Review/008 Review of Temporal Difference Learning.mp4 7.5 MB
02 Background Review/009 Review of Approximation Methods for Reinforcement Learning.mp4 3.8 MB
02 Background Review/010 Review of Deep Learning.mp4 11.6 MB
03 OpenAI Gym and Basic Reinforcement Learning Techniques/011 OpenAI Gym Tutorial.mp4 9.1 MB
03 OpenAI Gym and Basic Reinforcement Learning Techniques/012 Random Search.mp4 10.8 MB
03 OpenAI Gym and Basic Reinforcement Learning Techniques/013 Saving a Video.mp4 4.8 MB
03 OpenAI Gym and Basic Reinforcement Learning Techniques/014 CartPole with Bins Theory.mp4 6.3 MB
03 OpenAI Gym and Basic Reinforcement Learning Techniques/015 CartPole with Bins Code.mp4 15.4 MB
03 OpenAI Gym and Basic Reinforcement Learning Techniques/016 RBF Neural Networks.mp4 17.3 MB
03 OpenAI Gym and Basic Reinforcement Learning Techniques/017 RBF Networks with Mountain Car Code.mp4 14.4 MB
03 OpenAI Gym and Basic Reinforcement Learning Techniques/018 RBF Networks with CartPole Theory.mp4 3.2 MB
03 OpenAI Gym and Basic Reinforcement Learning Techniques/019 RBF Networks with CartPole Code.mp4 9.3 MB
03 OpenAI Gym and Basic Reinforcement Learning Techniques/020 Theano Warmup.mp4 6.1 MB
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Complete Python Bootcamp (Curso Udemy).rar 2.2 GB
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part00.mp4 466.1 MB
part01.mp4 182.6 MB
part02.mp4 568.4 MB
part03.mp4 833.9 MB
part04.mp4 2.2 GB
part05.mp4 1.9 GB
part06.mp4 1.9 GB
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11 Conclusion/attached_files/064 Course Summary and how to become an Expert/ResearchPapersandURLS.pdf 99.0 kB
01 Course Introduction and Setup/001 Introduction.mp4 12.2 MB
01 Course Introduction and Setup/002 Introduction to Computer Vision and OpenCV.mp4 7.5 MB
01 Course Introduction and Setup/003 About this course.mp4 10.8 MB
01 Course Introduction and Setup/004 OpenCV Python Installation Windows.mp4 25.1 MB
01 Course Introduction and Setup/005 Installation Mac.html 6.6 kB
01 Course Introduction and Setup/006 Installation Linux.html 4.4 kB
01 Course Introduction and Setup/007 Setting up our course materials.mp4 4.8 MB
02 Basics of Computer Vision and OpenCV/008 What are Images.mp4 4.6 MB
02 Basics of Computer Vision and OpenCV/009 Image Formation.mp4 6.5 MB
02 Basics of Computer Vision and OpenCV/010 Storing Images on Computers.mp4 11.4 MB
02 Basics of Computer Vision and OpenCV/011 Getting Started with OpenCV.mp4 24.8 MB
02 Basics of Computer Vision and OpenCV/012 Grayscaling.mp4 4.7 MB
02 Basics of Computer Vision and OpenCV/013 Color Spaces.mp4 32.1 MB
02 Basics of Computer Vision and OpenCV/014 Histograms.mp4 13.7 MB
02 Basics of Computer Vision and OpenCV/015 Drawing Images.mp4 10.3 MB
03 Image Manipulations/016 Transformations affine and non-affine.mp4 3.7 MB
03 Image Manipulations/017 Translations.mp4 5.2 MB
03 Image Manipulations/018 Rotations.mp4 6.3 MB
03 Image Manipulations/019 Scaling Re-sizing and Interpolations.mp4 9.1 MB
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01 Get Started/001 Outline and Motivation.mp4 7.5 MB
01 Get Started/002 Where to get the Code and Data.mp4 3.5 MB
01 Get Started/003 All Data is the Same.mp4 5.5 MB
01 Get Started/004 Plug-and-Play.mp4 3.7 MB
02 Bias-Variance Trade-Off/005 Bias-Variance Key Terms.mp4 10.7 MB
02 Bias-Variance Trade-Off/006 Bias-Variance Trade-Off.mp4 5.1 MB
02 Bias-Variance Trade-Off/007 Bias-Variance Decomposition.mp4 5.6 MB
02 Bias-Variance Trade-Off/008 Polynomial Regression Demo.mp4 43.8 MB
02 Bias-Variance Trade-Off/009 K-Nearest Neighbor and Decision Tree Demo.mp4 14.5 MB
02 Bias-Variance Trade-Off/010 Cross-Validation as a Method for Optimizing Model Complexity.mp4 7.3 MB
03 Bootstrap Estimates and Bagging/011 Bootstrap Estimation.mp4 15.9 MB
03 Bootstrap Estimates and Bagging/012 Bootstrap Demo.mp4 11.5 MB
03 Bootstrap Estimates and Bagging/013 Bagging.mp4 4.1 MB
03 Bootstrap Estimates and Bagging/014 Bagging Regression Trees.mp4 16.6 MB
03 Bootstrap Estimates and Bagging/015 Bagging Classification Trees.mp4 21.3 MB
03 Bootstrap Estimates and Bagging/016 Stacking.mp4 6.4 MB
04 Random Forest/017 Random Forest Algorithm.mp4 15.1 MB
04 Random Forest/018 Random Forest Regressor.mp4 15.6 MB
04 Random Forest/019 Random Forest Classifier.mp4 13.2 MB
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01 Outline Review and Logistical Things/001 Introduction Outline and Review.mp4 4.7 MB
01 Outline Review and Logistical Things/002 Where to get the code data for this course.mp4 3.3 MB
01 Outline Review and Logistical Things/003 How to Succeed in this Course.mp4 10.0 MB
02 Word Embeddings and Word2Vec/004 Alternative to Wikipedia Data Brown Corpus.mp4 13.1 MB
02 Word Embeddings and Word2Vec/005 What is a word embedding.mp4 18.9 MB
02 Word Embeddings and Word2Vec/006 Using pre-trained word embeddings.mp4 4.3 MB
02 Word Embeddings and Word2Vec/007 Word analogies using word embeddings.mp4 6.9 MB
02 Word Embeddings and Word2Vec/008 TF-IDF and t-SNE experiment.mp4 28.0 MB
02 Word Embeddings and Word2Vec/009 Word2Vec introduction.mp4 9.2 MB
02 Word Embeddings and Word2Vec/010 CBOW.mp4 4.4 MB
02 Word Embeddings and Word2Vec/011 Skip-Gram.mp4 6.6 MB
02 Word Embeddings and Word2Vec/012 Negative Sampling.mp4 14.2 MB
02 Word Embeddings and Word2Vec/013 Why do I have 2 word embedding matrices and what do I do with them.mp4 2.7 MB
02 Word Embeddings and Word2Vec/014 Word2Vec in Code with Numpy part 1.mp4 56.3 MB
02 Word Embeddings and Word2Vec/015 Word2Vec in Code with Numpy part 2.mp4 6.3 MB
02 Word Embeddings and Word2Vec/016 Converting a sequence of word indexes to a sequence of word vectors.mp4 5.7 MB
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02 Word Embeddings and Word2Vec/018 Word2Vec in Code with Theano.mp4 32.6 MB
03 Word Embeddings using GLoVe/019 Recommender systems and matrix factorization tutorial.mp4 19.9 MB
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03 Building Basic Spider with Scrapy/attached_files/006 Scrapy Simple Spider - Part 1/3.1.quotes-spider-basic.zip 6.7 kB
03 Building Basic Spider with Scrapy/attached_files/008 Scrapy Simple Spider - Part 3/3.3.quotes-spider-basic.zip 6.9 kB
04 XPath Syntax/attached_files/009 Using XPath with Scrapy/Xpath-introduction.zip 303 Bytes
06 Building More Advanced Spider with Scrapy/attached_files/012 Scrapy Advanced Spider - Part 1/4.quotes-spider-advanced.zip 26.3 kB
06 Building More Advanced Spider with Scrapy/attached_files/016 Scrapy Architecture/quotes-spider-v5-architecture.zip 7.1 kB
10 Logging into Websites Using Scrapy/attached_files/020 Logging into Websites Using Scrapy/quotes-spider-logging-in-video.zip 4.4 kB
11 Scrapy as a Standalone Script/attached_files/021 Scrapy as a Standalone Script/quotes-spider-runspider-command-video.zip 531 Bytes
12 Building Web Crawler with Scrapy/attached_files/022 Building Web Crawler with Scrapy/books-crawler.zip 4.2 kB
13 Scrapy with Selenium/attached_files/024 Selenium WebDriver Scrapy Selector to Extract URLs/Scrapy-with-Selenium-1.zip 4.3 kB
13 Scrapy with Selenium/attached_files/025 Selenium Loading Next for Data Extraction usable even with JavaScript pages/Scrapy-with-Selenium-2.zip 4.5 kB
14 Scrapy Spider - Books Store/attached_files/027 Grabbing URLs/Advanced-spider-books-1.zip 4.3 kB
14 Scrapy Spider - Books Store/attached_files/028 Data Extraction/Advanced-spider-books-2.zip 4.7 kB
15 More about Scrapy/attached_files/029 Scrapy Arguments/ScrapyArguments.zip 4.7 kB
15 More about Scrapy/attached_files/030 Scrapy Close Function/ScrapyCloseFunction.zip 4.8 kB
16 Export Output to Files/attached_files/031 Scrapy Feed Exports to CSV JSON or XML/ScrapyFeedExports.zip 126.7 kB
16 Export Output to Files/attached_files/032 Export Output to Excel/books-crawler-excel.zip 1.2 MB
18 Extracting Data to Databases - MySQL MongoDB/attached_files/042 Writing Data to MySQL/Writing-Data-to-MySQL.zip 4.9 kB
18 Extracting Data to Databases - MySQL MongoDB/attached_files/045 Writing Data to MongoDB/Writing-data-to-MongoDB.zip 4.8 kB
19 Scrapy Project 2 Web Scraping Course-Central.com/attached_files/046 Scraping Course-Central - Part 1 Subjects/class-central-spider-part1.zip 4.6 kB
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01 Introduction and Outline/001 Introduction and Outline.mp4 3.4 MB
01 Introduction and Outline/002 Where does this course fit into your deep learning studies.mp4 5.4 MB
01 Introduction and Outline/003 How to Succeed in this Course.mp4 10.0 MB
02 Principal Components Analysis/004 What does PCA do.mp4 12.1 MB
02 Principal Components Analysis/005 PCA derivation.mp4 7.0 MB
02 Principal Components Analysis/006 MNIST visualization finding the optimal number of principal components.mp4 9.8 MB
02 Principal Components Analysis/007 PCA objective function.mp4 3.9 MB
03 t-SNE t-distributed Stochastic Neighbor Embedding/008 t-SNE Theory.mp4 8.3 MB
03 t-SNE t-distributed Stochastic Neighbor Embedding/009 t-SNE on the Donut.mp4 15.8 MB
03 t-SNE t-distributed Stochastic Neighbor Embedding/010 t-SNE on XOR.mp4 9.8 MB
03 t-SNE t-distributed Stochastic Neighbor Embedding/011 t-SNE on MNIST.mp4 4.6 MB
04 Autoencoders/012 Autoencoders.mp4 6.1 MB
04 Autoencoders/013 Denoising Autoencoders.mp4 3.6 MB
04 Autoencoders/014 Stacked Autoencoders.mp4 6.9 MB
04 Autoencoders/015 Writing the autoencoder class in code Theano.mp4 40.4 MB
04 Autoencoders/016 Testing our Autoencoder Theano.mp4 11.9 MB
04 Autoencoders/017 Writing the deep neural network class in code Theano.mp4 44.0 MB
04 Autoencoders/018 Autoencoder in Code Tensorflow.mp4 25.6 MB
04 Autoencoders/019 Testing greedy layer-wise autoencoder training vs. pure backpropagation.mp4 19.4 MB
04 Autoencoders/020 Cross Entropy vs. KL Divergence.mp4 7.8 MB
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01 Introduction to Unsupervised Learning/001 Introduction and Outline.mp4 4.3 MB
01 Introduction to Unsupervised Learning/002 What is unsupervised learning used for.mp4 7.9 MB
01 Introduction to Unsupervised Learning/003 Why Use Clustering.mp4 7.0 MB
01 Introduction to Unsupervised Learning/004 How to Succeed in this Course.mp4 9.2 MB
02 K-Means Clustering/005 Visual Walkthrough of the K-Means Clustering Algorithm.mp4 5.1 MB
02 K-Means Clustering/006 Soft K-Means.mp4 4.4 MB
02 K-Means Clustering/007 The K-Means Objective Function.mp4 3.2 MB
02 K-Means Clustering/008 Soft K-Means in Python Code.mp4 31.7 MB
02 K-Means Clustering/009 Visualizing Each Step of K-Means.mp4 5.5 MB
02 K-Means Clustering/010 Examples of where K-Means can fail.mp4 17.8 MB
02 K-Means Clustering/011 Disadvantages of K-Means Clustering.mp4 4.1 MB
02 K-Means Clustering/012 How to Evaluate a Clustering Purity Davies-Bouldin Index.mp4 11.9 MB
02 K-Means Clustering/013 Using K-Means on Real Data MNIST.mp4 11.2 MB
02 K-Means Clustering/014 One Way to Choose K.mp4 9.5 MB
02 K-Means Clustering/015 K-Means Application Finding Clusters of Related Words.mp4 27.2 MB
03 Hierarchical Clustering/016 Visual Walkthrough of Agglomerative Hierarchical Clustering.mp4 4.6 MB
03 Hierarchical Clustering/017 Agglomerative Clustering Options.mp4 6.5 MB
03 Hierarchical Clustering/018 Using Hierarchical Clustering in Python and Interpreting the Dendrogram.mp4 12.4 MB
04 Gaussian Mixture Models GMMs/019 Description of the Gaussian Mixture Model and How to Train a GMM.mp4 5.5 MB
04 Gaussian Mixture Models GMMs/020 Comparison between GMM and K-Means.mp4 3.1 MB
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01 Introduction and Outline/001 Introduction and Outline Why would you want to use an HMM.mp4 7.1 MB
01 Introduction and Outline/002 Unsupervised or Supervised.mp4 5.5 MB
01 Introduction and Outline/003 Where to get the Code and Data.mp4 2.2 MB
01 Introduction and Outline/004 How to Succeed in this Course.mp4 9.2 MB
02 Markov Models/005 The Markov Property.mp4 8.7 MB
02 Markov Models/006 Markov Models.mp4 8.6 MB
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04 Hidden Markov Models for Discrete Observations/015 How can we choose the number of hidden states.mp4 7.7 MB
04 Hidden Markov Models for Discrete Observations/016 The Forward-Backward Algorithm.mp4 7.1 MB
04 Hidden Markov Models for Discrete Observations/017 Visual Intuition for the Forward Algorithm.mp4 6.3 MB
04 Hidden Markov Models for Discrete Observations/018 The Viterbi Algorithm.mp4 5.3 MB
04 Hidden Markov Models for Discrete Observations/019 Visual Intuition for the Viterbi Algorithm.mp4 6.0 MB
04 Hidden Markov Models for Discrete Observations/020 The Baum-Welch Algorithm.mp4 4.6 MB
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01 Introduction and Review/001 Introduction and Outline.mp4 8.0 MB
01 Introduction and Review/002 Review of Important Concepts.mp4 6.3 MB
01 Introduction and Review/003 Where to get the Code and Data.mp4 4.0 MB
01 Introduction and Review/004 How to Succeed in this Course.mp4 9.2 MB
02 K-Nearest Neighbor/005 K-Nearest Neighbor Concepts.mp4 9.0 MB
02 K-Nearest Neighbor/006 KNN in Code with MNIST.mp4 18.8 MB
02 K-Nearest Neighbor/007 When KNN Can Fail.mp4 8.1 MB
02 K-Nearest Neighbor/008 KNN for the XOR Problem.mp4 4.5 MB
02 K-Nearest Neighbor/009 KNN for the Donut Problem.mp4 5.7 MB
03 Naive Bayes and Bayes Classifiers/010 Naive Bayes.mp4 16.5 MB
03 Naive Bayes and Bayes Classifiers/011 Naive Bayes Handwritten Example.mp4 6.1 MB
03 Naive Bayes and Bayes Classifiers/012 Naive Bayes in Code with MNIST.mp4 15.1 MB
03 Naive Bayes and Bayes Classifiers/013 Non-Naive Bayes.mp4 7.7 MB
03 Naive Bayes and Bayes Classifiers/014 Bayes Classifier in Code with MNIST.mp4 4.7 MB
03 Naive Bayes and Bayes Classifiers/015 Linear Discriminant Analysis LDA and Quadratic Discriminant Analysis QDA.mp4 10.9 MB
03 Naive Bayes and Bayes Classifiers/016 Generative vs Discriminative Models.mp4 5.4 MB
04 Decision Trees/017 Decision Tree Basics.mp4 8.7 MB
04 Decision Trees/018 Information Entropy.mp4 7.3 MB
04 Decision Trees/019 Maximizing Information Gain.mp4 14.6 MB
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01 Start Here/quizzes/001 Easy first quiz.html 2.5 kB
01 Start Here/001 Introduction and Outline.mp4 7.9 MB
01 Start Here/002 How to Succeed in this Course.mp4 9.2 MB
01 Start Here/003 Review of the classification problem.mp4 3.1 MB
01 Start Here/004 Introduction to the E-Commerce Course Project.mp4 15.5 MB
02 Basics What is linear classification Whats the relation to neural networks/005 Linear Classification.mp4 7.9 MB
02 Basics What is linear classification Whats the relation to neural networks/006 Biological inspiration - the neuron.mp4 4.4 MB
02 Basics What is linear classification Whats the relation to neural networks/007 How do we calculate the output of a neuron logistic classifier - Theory.mp4 7.8 MB
02 Basics What is linear classification Whats the relation to neural networks/008 How do we calculate the output of a neuron logistic classifier - Code.mp4 6.1 MB
02 Basics What is linear classification Whats the relation to neural networks/009 E-Commerce Course Project Pre-Processing the Data.mp4 11.7 MB
02 Basics What is linear classification Whats the relation to neural networks/010 E-Commerce Course Project Making Predictions.mp4 6.0 MB
03 Solving for the optimal weights/011 A closed-form solution to the Bayes classifier.mp4 10.5 MB
03 Solving for the optimal weights/012 What do all these symbols mean X Y N D L J PY1X etc..mp4 6.7 MB
03 Solving for the optimal weights/013 The cross-entropy error function - Theory.mp4 4.7 MB
03 Solving for the optimal weights/014 The cross-entropy error function - Code.mp4 9.5 MB
03 Solving for the optimal weights/015 Visualizing the linear discriminant Bayes classifier Gaussian clouds.mp4 5.5 MB
03 Solving for the optimal weights/016 Maximizing the likelihood.mp4 13.3 MB
03 Solving for the optimal weights/017 Updating the weights using gradient descent - Theory.mp4 9.8 MB
03 Solving for the optimal weights/018 Updating the weights using gradient descent - Code.mp4 7.6 MB
03 Solving for the optimal weights/019 E-Commerce Course Project Training the Logistic Model.mp4 17.9 MB
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code/urllib2_randomuseragent.py 1.1 kB
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code/urllib2_urlencode.py 756 Bytes
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01 Introduction and Outline/001 Whats this course all about.mp4 3.9 MB
01 Introduction and Outline/002 Where to get the code for this course.mp4 2.1 MB
01 Introduction and Outline/003 How to succeed in this course.mp4 5.8 MB
02 Bayes Rule and Probability Review/004 Bayes Rule Review.mp4 15.4 MB
02 Bayes Rule and Probability Review/005 Simple Probability Problem.mp4 3.4 MB
02 Bayes Rule and Probability Review/006 The Monty Hall Problem.mp4 6.3 MB
02 Bayes Rule and Probability Review/007 Imbalanced Classes.mp4 7.5 MB
02 Bayes Rule and Probability Review/008 Maximum Likelihood - Mean of a Gaussian.mp4 8.0 MB
02 Bayes Rule and Probability Review/009 Maximum Likelihood - Click-Through Rate.mp4 7.1 MB
02 Bayes Rule and Probability Review/010 Confidence Intervals.mp4 16.6 MB
02 Bayes Rule and Probability Review/011 What is the Bayesian Paradigm.mp4 10.4 MB
03 Traditional AB Testing/012 AB Testing Problem Setup.mp4 7.3 MB
03 Traditional AB Testing/013 Simple AB Testing Recipe.mp4 8.2 MB
03 Traditional AB Testing/014 P-Values.mp4 6.5 MB
03 Traditional AB Testing/015 Test Characteristics Assumptions and Modifications.mp4 11.0 MB
03 Traditional AB Testing/016 t-test in Code.mp4 6.2 MB
03 Traditional AB Testing/017 0.01 vs 0.011 - Why should we care.mp4 2.9 MB
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03 Traditional AB Testing/020 ABCD... Testing - The Bonferroni Correction.mp4 3.8 MB
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