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Nov 26, 2017


Learning Philosophy:

Have basic business understanding

Be familiar with how ML is applied at other companies

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

Be able to perform feature selection and 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 setup project structure

Be able to version control code

Be able to version control data

Be able to use experiment management tools

Be able to setup model validation

Be familiar with inner working of models

Be able to improve model generalization

Be familiar with fundamental ML concepts

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 multi-modal machine learning

Be familiar with Recommendation Systems

Be able to implement computer vision models

Be familiar with graphs and network data

Be familiar with timeseries and forecasting

Be familiar with basics of Reinforcement Learning

Be able to perform hyperparameter tuning

Be familiar with literature on model interpretability

Be able to optimize models for inference

Be able to write unit tests

Be familiar with ML System Design

Be able to serve ML models

Be able to setup batch inference

Be able to build interactive UI for models

Be able to use Docker for containerization

Be able to use Cloud

Be familiar with serverless architecture

Be able to monitor ML models

Be able to perform load testing

Be able to perform A/B testing

Be proficient in Python

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