https://github.com/shenweichen/coursera

Quiz & Assignment of Coursera
https://github.com/shenweichen/coursera

computer-vision coursera data-science data-structures deep-learning machine-learning natural-language-processing reinforcement-learning

Last synced: 4 days ago
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Quiz & Assignment of Coursera

• Host: GitHub
• URL: https://github.com/shenweichen/coursera
• Owner: shenweichen
• Created: 2016-06-30T04:31:41.000Z (over 8 years ago)
• Default Branch: master
• Last Pushed: 2020-12-20T09:32:52.000Z (about 4 years ago)
• Last Synced: 2024-10-14T21:10:31.178Z (4 months ago)
• Topics: computer-vision, coursera, data-science, data-structures, deep-learning, machine-learning, natural-language-processing, reinforcement-learning
• Language: Jupyter Notebook
• Homepage:
• Size: 71.9 MB
• Stars: 870
• Watchers: 54
• Forks: 659
• Open Issues: 7
• Metadata Files:
  • Readme: README.md

Awesome Lists containing this project

README

        
# Coursera Assignments

This repository is aimed to help Coursera learners who have difficulties in their learning process.  

The quiz and programming homework is belong to coursera.Please **Do Not** use them for any other purposes.  

Please feel free to contact me if you have any problem,my email is [email protected].

* [Bayesian Statistics From Concept to Data Analysis](./Bayesian_Statistics_From_Concept_to_Data_Analysis_UC_Santa_Cruz)

* [Learn to Program: Crafting Quality Code](./Learn_to_Program_Crafting_Quality_Code_University_of_Toronto)

* [Neural Networks for Machine Learning-University of Toronto](./Neural_Networks_for_Machine_Learning_University_of_Toronto)

* Specialization Advanced Machine Learning Higher School of Economics

  * Introduction to Deep Learning

* [Specialization Applied Data Science with Python](./Specialization_Applied_Data_Science_with_Python_University_of_Michigan)

  * Introduction to Data Science in Python

  * Applied Machine Learning in Python

* [Specialization Big Data-UCSD](./Specialization_Big_Data_UC_San_Diego)

  * Introduction to Big Data

  * Big Data Modeling and Management Systems

  * Big Data Interation and Processing

* [Specialization Data Mining-UIUC](./Specialization_Data_Mining_UIUC)

  * Text Retrieval and Search Engines

  * Text Mining and Analytics

  * Pattern Discovery in Data Mining

  * Cluster Analysis in Data Mining

* [Specialization Data Science-Johns Hopkins University](./Specialization_Data_Science_Johns_Hopkins_University)

  * The Data Scientist’s Toolbox

  * R Programming

  * Getting and Cleaning Data

* [Specialization Data Structures & Algorithms-UC San Diego](./Specialization_Data_Structures_Algorithms_UC_San_Diego)

  * Algorithmic Toolbox

  * Data Structures

  * Algorithms on Graphs

  * Algorithms on Strings

* [Specialization Deep Learning](./Specialization_Deep_Learning_deeplearning.ai)

  * Neural Networks and Deep Learning

  * Improving Deep Neural Networks Hyperparameter tuning, Regularization and Optimization

  * Structuring Machine Learning Projects

  * Convolutional Neural Networks

  * Sequence Models

* [Specialization Functional Programming in Scala](./Specialization_Functional_Programming_in_Scala)

  * Functional Programming Principles in Scala

* Specialization Fundamentals of Computing-Rice University

  * Principles of Computing 1

* [Specialization Meachine Learning-University of Washington](./Specialization_Machine_Learning_University_of_Washington)

  * Machine Learning Foundations: A Case Study Approach

  * Machine Learning: Regression

  * Machine Learning: Classification

  * Machine Learning: Clustering & Retrieval

* [Specialization Probabilistic Graphical Models-Stanford University](./Specialization_Probabilistic_Graphical_Models_Stanford_University)

  * Probabilistic Graphical Models 1: Representation

  * Probabilistic Graphical Models 2: Inference

  * Probabilistic Graphical Models 3: Learning

* [Specialization 程序设计与算法-Peking University](./Specialization_Program_Design_Algorithm_Peking_University)

  * 计算导论与C语言基础

  * C程序设计进阶

  * C++程序设计

  * 算法基础

  * 数据结构基础

* [Specialization Recommender System-University of Minnesota](./Specialization_Recommender_System_University_of_Minnesota)

  * Introduction to Recommender Systems: Non-Personalized and Content-Based

  * Nearest Neighbor Collaborative Filtering

  * Recommender Systems:Evaluation and Metrics

  * Matrix Factorization and Advanced Techniques

* [Specialization Statistics with R-Duke University](./Specialization_Statistics_with_R_Duke_University)

  * Introduction to Probability and Data

  * Inferential Statistics

* [The Unix Workbench-Johns Hopkins University](./The_Unix_Workbench_Johns_Hopkins_University)