Deep Learning | The AI buddy

Best Machine Learning Books in 2022

This article covers the best books that exist in Machine Learning today and we will be discussing the best book depending on the exposure.

Google Announces Objectron Dataset - Code, Dataset inside

Machine learning has reached the state of the art in many of it's computer vision applications be it Object Detection, Image...

Deep Learning Course by Yann LeCun at NYU is Free! Details Inside

This course involves latest technologies in deep learning, representative learning.

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Best Image Datasets for Machine Learning and Data Science (ML002)

In this post I will be discussing about Machine learning datasets in particular. Some people might start with algorithms in the beginning...

Getting started with Generative Adversarial Networks(GANs)

eep learning algorithms have come a long way in the last few decades which is due to the powerful processors and abundance of data.

Can Convolutional Neural Networks(CNNs) become the next big thing in AI?

From building a face detection system to a self-driving car, all these applications use Convolutional Neural Network as the base model.

Squeeze-Net — Model size of 0.5MB, and accuracy same as AlexNet

SqueezeNet achieves AlexNet-level accuracy on ImageNet with50x fewer parameters.

Hands-on with Tensorflow 2.0 - Part I

In Tensorflow 2.0, we say goodbye to tf.session(), and it has come with tf.keras API as a part of it. Moreover, it runs on eager mode.

CNN Architecture Series — Hands on with AlexNet(Part II)

Welcome to Part II of the CNN architecture series, I hope you liked Part I of this series which was based on VGG-16. Today, we will...

Deep Learning Architectures Series — Hands on with VGG-16(Part-I)

We will take a in-depth look at all the standard CNN architectures, let it be as simple as VGG-16 or as complex as Xception. In today’s worl