Ritiz Saini's Projects
The aim of this project is to use VHDL to implement a multi-cycle processor which is an 8-register, 16-bit computer system which uses point-to-point communication infrastructure ( for e.g. A 16-bit very simple computer developed for the teaching purpose). The IITB-Proc is general enough to solve complex problems.
My solutions for the algorithmic toolbox course on Coursera
A Jekyll theme for automatically generating and deploying landing page sites for mobile apps.
OpenCV Python Neural Network Autonomous RC Car
An awesome README template to jumpstart your projects!
The 3rd edition of course.fast.ai
Homework from the deeplearning.ai Deep Learning Specialization on Coursera
crakx.github.io
A starter template for Equinor data science / data engineering projects
Materials from deeplearning.ai course on Coursera
This repository contains my personal notes and summaries on DeepLearning.ai specialization courses. I've enjoyed every little bit of the course hope you enjoy my notes too.
Equation plotter a software that plots the graph of y = f(x) function which is inputted by the user on the console screen. The software will also provide the user data about the critical points, inflection points, roots of the function and it will also provide the user the graphs of the function’s integral & differential on his/her will. If the user will be able to see them together.
All of my open source flutter and dart projects, tutorials are published here.
It was built a web application as a step forward in building a 3D recommendation system.
This project includes implementation of various operations using microprocessor
This neural network can tell you which other ingredients you can add to your cooking recipes to improve them. It's trained on the [simplified-recipes-1M dataset](https://dominikschmidt.xyz/simplified-recipes-1M) which differentiates between 3500 different ingredients
Like Prometheus, but for logs.
Explanation to key concepts in ML
ritizsaini.github.io
Classification of URLs using Machine Learning Techniques like Logistic Regression, Naive Bayes, Support Vector Machine, 4 Layer neural network An increase of more than 2 percent in accuracy was obtained by using probability attributes of Naive bayes
Everything in this universe dont need any description
Python programs to practice or demonstrate skills.
VIP cheatsheets for Stanford's CS 230 Deep Learning
Using Deep Learning Techniques to generate moving videos from still images, by realistic interpolation of the initial and final image, considering the challenge of memory limitations due to huge pixel sizes of the images. Our approach was based on the following two papers, mainly on [1]; [1] Haoye Cai, Chunyan Bai, Yu-Wing Tai, and Chi-Keung Tang. Deep video generation, prediction and completion of human action sequences. In Proceedings of the European Conference on Computer Vision (ECCV) [2] Yunpeng Li, Dominik Roblek, and Marco Tagliasacchi. From here to there: Video inbetweening using direct 3d convolutions. arXiv preprint arXiv:1905.10240, 2019
, I'm Ritiz Saini!
React
Typescript
Django
Laravel
Facebook
Microsoft
Google
Alibaba
D3
Tencent