The two popular deep-learning frameworks, TensorFlow and PyTorch, support NVIDIA’s GPUs for acceleration via the CUDA toolkit. This poses a problem for deep-learning development on Macs.

But not anymore!

Along with the latest release of its custom made Silicon Chips based on the ARM Architecture, Apple announced a new ML Compute framework which can be used for accelerated training of ML and DL Models taking advantage of the GPUs present on the Apple Macs without the need of CUDA support.

We now have a Mac-optimized version of Tensorflow 2.4 which we can be installed on both the older Intel-powered Macs…


In this post we will train a multi-class image classification model using deep learning techniques that accurately classifies the images into one of the 5 weather categories: Sunrise, Cloudy, Rainy, Shine, or Foggy. We will implement this project in PyTorch.

PyTorch is a widely used, open source deep learning platform developed by Facebook for easily writing neural network layers in Python enabling a seamless workflow from research to production. It is also one of the preferred deep learning research platforms built to provide maximum flexibility and speed.

We have downloaded this weather dataset from Kaggle for creating our classification model…


In today’s world, machine learning plays a crucial role in the sector of banking and finance. A more personalized and smarter data-driven approach of targeting customers is needed so that the organizations can reduce their marketing expenditure and at the same time, derive better results.

In this post we will build Machine Learning models to predict success of the marketing campaigns of a Portuguese banking institution. The goal of these models is to predict whether a customer will subscribe to a term deposit based on various factors like client personal details, marketing campaign details and other social and economic factors.

About the Dataset:

Chirag Daryani

A Computer Science undergraduate student who is always eager to learn new things!

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