This learning path is aimed toward those people who want to become a data scientist in 2019, and includes resources like courses, guides and much more!
What a year it has been for data science. Here’s our pick of the best and most popular articles that were published on Analytics Vidhya in 2018.
2018 was a HUGE year in open source machine learning projects. Here’s our pick of the bunch, with projects divided into different categories.
A Technical Overview of AI & ML (NLP, Computer Vision, Reinforcement Learning) in 2018 & Trends for 2019
From Google’s BERT to Facebook’s PyTorch, 2018 was a HUGE year in ML. Find out what else made the news and what to look forward to in the new year!
This article covers the top three solutions shared by the winners for WNS online hackathon conducted on 14th-16th September.
This article is a collection of the most useful machine learning and deep learning GitHub repositories and Reddit discussions created in November 2018.
Building a Random Forest from Scratch & Understanding Real-World Data Products (ML for Programmers – Part 3)
This article covers different industry applications where a machine learning model can be implemented and necessary steps to follow in building a model.
This detailed article covers an introduction to the Monte Carlo Method of learning using the popular OpenAI Gym library – with Python implementation!
This article lists down the most awesome machine learning and deep learning GitHub repositories and Reddit discussions from October 2018!
An Intuitive Guide to Interpret a Random Forest Model using fastai library (Machine Learning for Programmers – Part 2)
A summary of fast.ai’s course that interprets the results of a random forest model using various techniques like partial dependence & tree interpreters.