Data Science Learning
Repository of code, resources and utilities related to different data science and machine learning topics. For learning, practicing and teaching purposes.
Utils can be installed via
python setup.py develop
Data Science Resources
resources.md provides a list of suggested resources (e.g. books, courses) grouped by topic (e.g. mathematics, deep learning, NLP). This list is based on my informal research between online communities and practitioners for the various topics, and then supported by personal notes once I've manage to consume the resource and come up with my own opinion about its quality and content. Tags like TOREAD and TOCHECK express exactly that I still didn't have the time to properly check the related entry.
Jupyter Notebooks
Many of the resources entries are personal Jupyter notebooks that contain a mix of textual explanations, references, comments and code examples about the discussed topic.
Notebook can be in different states and have different purposes, some are polished in content, with complete explanations, proper structure and working code. These I consider to have the potential to be useful to others for learning. Some have been started and worked on with the same goal, but are not polished for consumption [WIP].A third type of content is about notebooks where I simply play around with code for testing/practicing personal ideas [DEV]. While I often try to comment code snippets, these notebooks might have a more chaotic structure and miss properly cured discussions about the topic and techniques used.
Statistics
Machine Learning
- Linear Regression - Basics
- Logistic Regression
- Evaluation Metrics
- Tensorflow - Intro [WIP]
- Markov Models [WIP]
Deep Learning
- Autoencoders
- GANs - Intro
- GANs - DCGAN
- GANs - ProGAN [WIP]
- GANs - StyleGAN
- Style Transfer [WIP]
- CPPN
- Sketch Cleanup [DEV]
Computer Vision
NLP
- RNN with Keras - Text Generation (Dedicated Repository)
- Text Clustering
- RNN Text Generation - Advanced (Dedicated Repository)
- Words Embedding [DEV]
Miscellaneous
- Data Manipulation and Visualization with Pandas and Seaborn — A Practical Introduction
- Sorting
- Data Viz
- Advanced Python [DEV]
Graphics
License
Released under version 2.0 of the Apache License.
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数据是新的石油。 该声明显示了如何通过捕获，存储和分析满足各种需求的数据来驱动每个现代IT系统。 无论是为商业做出决定，预测天气，研究生物学中的蛋白质结构还是设计营销活动。 所有这些情景都涉及使用数学模型，统计数据，图表，数据库以及数据分析背后的商业或科学逻辑的多学科方法。 因此，我们需要一种能够满足数据科学所有这些不同需求的编程语言。 Python就像一种语言一样闪亮，因为它拥有众多的库和内置功
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Complete-Data-Science-Toolkits The overall objective of this toolkit is to provide and offer a free collection of data analysis and machine learning that is specifically suited for doing data science.
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DATA-SCIENCE-BOWL-2018 Find the nuclei in divergent images to advance medical discovery Spot Nuclei. Speed Cures. Imagine speeding up research for almost every disease, from lung cancer and heart dise
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Best Data Science Resources Hey, Data Enthusiasts out there! Finally, after lots of requests from the community I finally came up with the best free Data Science Resouces which will equip you with all
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Data Science Collected Resources A trove of carefully curated resources and links (on the topics of software, platforms, language, techniques, etc.) related to data science, all in one place. Please f
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data-science-ipython-notebooks Index deep-learning tensorflow theano keras caffe scikit-learn statistical-inference-scipy pandas matplotlib numpy python-data kaggle-and-business-analyses spark mapredu