Part 1 Since childhood, we have been learning these creepy mathematical concepts like Algebra, Calculus, Statistics, and Probability. Have you ever asked yourself why? And How will these things help you in the future? Today I am going to help you out with that. These mathematical concepts play a very…

1000x more potent than BERT BERT — Bidirectional Encoder Representations from Transformers, also developed by Google What is Google’s MUM? MUM stands for Multitask Unified Model and is an AI-powered technology for answering complex questions that don’t have answers. MUM is a language model built on the same transformer system as BERT. BERT is…

The hottest field of the 22nd Century The term “Data Science” was coined by William S at the beginning of the 21st Century. The steps involved in the lifecycle of a data science project: Business Understanding Data Collection or Data Gathering Feature Engineering Feature Selection Model Creation & Hyper Parameter…

For Image Processing What is Data Augmentation and Why it is needed? Data Augmentation is a technique used to generate new samples from the existing data by using simple geometric transforms such as: Rotations Flips (Horizontal and Vertical) Shifts (Width and Height) Brightness Zoom Noise Why do Data Augmentation? If you have a small dataset and want to train…

Man Vs Machine Watching Sci-Fi movies is fun, but it starts to become a reality. Artificial Intelligence is slowly shaping our future. I best describe Artificial Intelligence as the simulation of human intelligence in computers or machines programmed to think like humans and mimic their actions. Now Artificial Intelligence is…

Making Future Now we have already entered the third phase of Natural Language Processing. It's like the wait is over. After this hype of Artificial Intelligence, we see chatbots everywhere to make the work easy. What are Chatbots? A chatbot is artificial intelligence software designed to stimulate conversation with human users, especially over…

Understanding of a Convolutional Neural Networks(CNN's |ConvNets) Convolutional Neural Networks are used mainly for image processing, classification, recognition, segmentation, and other autocorrelated data because of their high accuracy. What is Convolution? It is a mathematical combination of two functions to produce a third function. Layers used to build CNN's Convolutional Layer Pooling Layer Fully Connected Layer

For Complicated Distributions AutoEncoder The process of making the input data with high dimensionality into smaller after passing through the Neural Network. AutoEncoder Types: Denoising autoencoder. Sparse Autoencoder. Deep Autoencoder. Contractive Autoencoder. Undercomplete Autoencoder. Convolutional Autoencoder. Variational Autoencoder. There are so many techniques in machine learning to reduce the dimensionality of the data…