Top 5 Github Repos to Learn Data Science/ AI (or copy some code!)


1. Awesome Data Science
By: Fatih Aktürk, Hüseyin Mert & Osman Ungur, Recep Erol.
https://lnkd.in/g9VRjip

2. data-scientist-roadmap
By: MrMimic
https://lnkd.in/gBRwKVw

3. Data Science Best Resources
By: Tirthajyoti Sarkar
https://lnkd.in/ghk3yBd

4. Ds-cheatsheets
By: Favio André Vázquez
https://lnkd.in/gJHjc5X

5. DataScienceResources
By: jb
https://lnkd.in/gfn6GxN

🗣 @AI_Python_arXiv
✴️ @AI_Python_EN
❇️ @AI_Python

How Does NLP Benefit Legal System: A Summary of Legal Artificial Intelligence

https://github.com/thunlp/LegalPapers

Paper:
https://arxiv.org/abs/2004.12158v2

Jukebox: a new generative model for audio from OpenAI.

Jukebox, a model that generates music with singing in the raw audio domain.

openai.com/blog/jukebox

Article: cdn.openai.com/papers/jukebox.pdf

Examples: https://jukebox.openai.com/

Code: https://github.com/openai/jukebox

Reinforcement Learning with Augmented Data

https://mishalaskin.github.io/rad

Code: https://github.com/MishaLaskin/rad

Paper: https://arxiv.org/abs/2004.14990

An NLU-Powered Tool to Explore COVID-19 Scientific Literature

https://ai.googleblog.com/2020/05/an-nlu-powered-tool-to-explore-covid-19.html

Beneath the Tip of the Iceberg: Current Challenges and New Directions in Sentiment Analysis Research

Awesome Sentiment Analysis papers: https://github.com/declare-lab/awesome-sentiment-analysis

Paper: https://arxiv.org/abs/2005.00357v1

Set of Machine Learning Python plugins for GIMP


Github: https://github.com/kritiksoman/GIMP-ML

Paper: https://arxiv.org/abs/2004.13060

Demo: https://www.youtube.com/watch?v=HVwISLRow_0

🗣 @AI_Python_arXiv
✴️ @AI_Python_EN
❇️ @AI_Python

How to Create a Web API using Flask and Python

https://www.i2tutorials.com/how-to-create-a-web-api-using-flask-and-python/

Announcing Meta-Dataset: A Dataset of Datasets for Few-Shot Learning

https://ai.googleblog.com/2020/05/announcing-meta-dataset-dataset-of.html

Statistical Imputation for Missing Values in Machine Learning

https://machinelearningmastery.com/statistical-imputation-for-missing-values-in-machine-learning/

New Data Scientists - When you learn, it's easy to get distracted by Machine Learning & Deep Learning terms like "XGBoost", "Neural Networks", "RNN", "LSTM" or Advanced Technologies like "Spark", "Julia", "Scala", "Go", etc.

Don't get bogged down trying to learn every new term & technology you come across.

Instead, focus on foundations.
- data wrangling
- visualizing
- exploring
- modeling
- understanding the results.


Build yourself up. You'll advance much faster.

🗣 @AI_Python_arXiv
✴️ @AI_Python_EN
❇️ @AI_Python

XCOPA, a dataset for commonsense reasoning and knowledge transfer across 11 languages (including Quechua and Haitian Creole).

Download:
http://github.com/cambridgeltl/xcopa
Paper:
http://ducdauge.github.io/files/xcopa.pdf

🗣 @AI_Python_arXiv
✴️ @AI_Python_EN
❇️ @AI_Python

Introducing Jukebox, a neural net that generates music, including rudimentary singing, as raw audio in a variety of genres and artist styles. We're releasing a tool for everyone to explore the generated samples, as well as the model and code: https://openai.com/blog/jukebox/

🗣 @AI_Python_arXiv
✴️ @AI_Python_EN
❇️ @AI_Python

Free Live Course: Deep Learning with PyTorch

https://www.freecodecamp.org/news/free-deep-learning-with-pytorch-live-course/

video: https://www.youtube.com/watch?v=vo_fUOk-IKk

🗣 @AI_Python_arXiv
✴️ @AI_Python_EN
❇️ @AI_Python

Introduction to Neural Networks in Python | Tensorflow/Keras

https://morioh.com/p/abae4875bdd2/

SymJAX: symbolic CPU/GPU/TPU programming.

docs: https://symjax.readthedocs.io/en/latest/

github: https://github.com/RandallBalestriero/SymJAX

pdf: https://arxiv.org/pdf/2005.10635v1.pdf

Evaluating Natural Language Generation with BLEURT

BLEURT (Bilingual Evaluation Understudy with Representations from Transformers)

https://ai.googleblog.com/2020/05/evaluating-natural-language-generation.html

Github: https://github.com/google-research/bleurt

Paper: https://arxiv.org/abs/2004.04696

Tensorflow vs PyTorch for Text Classification using GRU

https://medium.com/@rodolfosaldanha_71881/tensorflow-vs-pytorch-for-text-classification-using-gru-e95f1b68fa2d

CVML web lecture series on basics of deep learning. Registration required (June 3rd)
Deep Learning: Convolutional Neural Networks
Deep Object Detection

http://icarus.csd.auth.gr/cvml-web-lecture-series/