There are an abundance of ML tools available today.

For beginners, this can be overwhelming.

This article from Analytics India Magazine asks the top Kagglers for their favorite toolsets.

In the next section, we look at the top tools, frameworks, cloud services, libraries used by the Kaggle masters and Grand Masters, which they revealed to us in our exclusive interviews. That said, we have to admit that all these top Kagglers are of the opinion that one should not fall in love with tools, and it is all right as long any tools get the job done right!

The Career Force goes through her top 5 free dataset resources in this video.

  1. is a large dataset aggregator and the home of the US Government’s open data.
  2. FiveThirtyEight: This is a great resource to not only see datasets, but also see how a well-respected analytics organization provides meaningful insights and commentary on the data.
  3. Kaggle:  is a great resource not only for free datasets, but for data science topics in general.
  4. Data.World: There are hundreds of thousands of free datasets for anyone that sets up an account on
  5. Google Dataset Search: By accessing thousands of different repositories across the web, Google Dataset Search provides access to almost 25 million different publicly available datasets.

Here’s an interesting tutorial for Keras and TensorFlow that predicts employee retention.

In this tutorial, you’ll build a deep learning model that will predict the probability of an employee leaving a company. Retaining the best employees is an important factor for most organizations. To build your model, you’ll use this dataset available at Kaggle, which has features that measure employee satisfaction in a company. To create this model, you’ll use the Keras sequential layer to build the different layers for the model.