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About the developer

amitness
3.3K Stars 543 Forks MIT License 842 Commits 1 Opened issues

Description

Becoming better at data science every day

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Contributors list

# 10,123
ml
udacity
gamific...
openapi
816 commits
# 316,106
Node.js
Kuberne...
learnin...
udacity
1 commit

learning

Learning Philosophy: - The Power of Tiny Gains - Master Adjacent Disciplines - T-shaped skills - Data Scientists Should Be More End-to-End - Just in Time Learning

Index

Have basic business understanding

Be able to frame an ML problem

Be familiar with data ethics

Be able to import data from multiple sources

Be able to setup data annotation efficiently

Be able to manipulate data with Numpy

Be able to manipulate data with Pandas

Be able to manipulate data in spreadsheets

Be able to manipulate data in databases

Be able to use Linux tools

Be able to perform feature engineering

Be able to experiment in a notebook

Be able to visualize data

Be able to do literature review using research papers

Be able to model problems mathematically

Be able to structure machine learning projects

Be able to version control code

Be able to version control data

Be familiar with fundamentals of ML and DL

Be able to implement models in scikit-learn

Be able to implement models in Tensorflow and Keras

Be able to implement models in PyTorch

Be able to implement models using cloud services

Be able to apply unsupervised learning algorithms

Be able to implement NLP models

Be familiar with Recommendation Systems

Be able to implement computer vision models

Be able to model graphs and network data

Be able to implement models for timeseries and forecasting

Be familiar with Reinforcement Learning

Be able to optimize performance metric

Be familiar with literature on model interpretability

Be able to optimize model size for production

Be able to write unit tests

Be able to serve models via APIs

Be able to build interactive UI for models

Be able to deploy model to production

Be able to perform load testing

Be able to perform A/B testing

Be proficient in Python

Be familiar with compiled languages

Have a general understanding of other parts of the stack

Be familiar with fundamental Computer Science concepts

Be able to apply proper software engineering process

Be able to efficiently use a text editor

Be able to communicate and collaborate well

Be familiar with the hiring pipeline

Broaden Perspective

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