Intro and Resources

• Book: https://github.com/oreilly-japan/deep-learning-from-scratch

• kaggle learning resource https://www.kaggle.com/learn/overview

  • Python Learn the most important language for data science.

  • Intro to Machine Learning Learn the core ideas in machine learning, and build your first models.

  • Intermediate Machine Learning Learn to handle missing values, non-numeric values, data leakage and more. Your models will be more accurate and useful.

  • Data Visualization Make great data visualizations. A great way to see the power of coding!

  • Pandas Solve short hands-on challenges to perfect your data manipulation skills.

  • Feature Engineering Discover the most effective way to improve your models.

  • Deep Learning Use TensorFlow to take machine learning to the next level. Your new skills will amaze you.

  • Intro to SQL Learn SQL for working with databases, using Google BigQuery to scale to massive datasets.

  • Advanced SQL Take your SQL skills to the next level.

  • Geospatial Analysis Create interactive maps, and discover patterns in geospatial data.

  • Microchallenges Solve ultra-short challenges to build and test your skill.

  • Machine Learning Explainability Extract human-understandable insights from any machine learning model.

  • Natural Language Processing Distinguish yourself by learning to work with text data

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Installation

GitHub - aron3312/embedding2lm: An introduction of the development from encoding(One hot, tf-idf......) to embedding(Word2vec,Glove,Fasttext......) and language model(Elmo, GPT2, BERT......) Requirement and StarGitHub