Ravi Yadav's Projects
This website is developed as a coursework for the "Adaptive Application" module in Trinity College Dublin.
Reading list for the Advanced Machine Learning Course
Learned about search problems (A*, CSP, minimax), reinforcement learning, bayes nets, hidden markov models, and machine learning
This repository is part of the coursework CS7IS2 contributed by Ankit, Ravi, Rohit.
An adversarial example library for constructing attacks, building defenses, and benchmarking both
The repository contains the visualization developed in Tableau.
A complete computer science study plan to become a software engineer.
This repository contains the project as part of the company interview process.
Class notes for CS 131.
Exercise notebooks for CVND.
A library containing both highly optimized building blocks and an execution engine for data pre-processing in deep learning applications
This repository contains the code for the assignment of Data Visualization module in Trinity College Dublin.
This repository contains visualization of CO2 emission by top 10 countries. The code was written as part of module Data Visualization in Trinity College Dublin.
practice
The Leek group guide to data sharing
Drench yourself in Deep Learning, Reinforcement Learning, Machine Learning, Computer Vision, and NLP by learning from these exciting lectures!!
The Web framework for perfectionists with deadlines.
Online Examination Portal
This repository contains the files used to implement a text editor
Excercises for people who're trying to learn Erlang
The repository is completed as part of assessment for the Job Interview.
A robot powered training repository :robot:
How to Make a Computer Operating System in C++
The goal of this course is to give learners basic understanding of modern neural networks and their applications in computer vision and natural language understanding. The course starts with a recap of linear models and discussion of stochastic optimization methods that are crucial for training deep neural networks. Learners will study all popular building blocks of neural networks including fully connected layers, convolutional and recurrent layers. Learners will use these building blocks to define complex modern architectures in TensorFlow and Keras frameworks. In the course project learner will implement deep neural network for the task of image captioning which solves the problem of giving a text description for an input image. The prerequisites for this course are: 1) Basic knowledge of Python. 2) Basic linear algebra and probability.
Learn OpenCV : C++ and Python Examples
LLCD is a simple python scraper tool that downloads video lessons from Linkedin Learning
A complete daily plan for studying to become a machine learning engineer.
React
Typescript
Django
Laravel
Facebook
Microsoft
Google
Alibaba
D3
Tencent