Pinned Repositories
Instantutor
AB-Testing
A/B Testing — A complete guide to statistical testing
cookiecutter-data-science
A logical, reasonably standardized, but flexible project structure for doing and sharing data science work.
CSCI-4967-Projects-in-ML-AI
This repo has the course material for Projects in ML/AI Course for Spring 2024
CSCI4962-Projects-ML-AI
This repo has the Lecture material for the course: projects in ML and AI
Instantutor
Peer-to-peer tutoring App
Projects-in-Machine-Learning-and-AI
RecSysResearch
tensorflow-deep-learning
All course materials for the Zero to Mastery Deep Learning with TensorFlow course.
ZTM-DS-and-Algo-Python
Contains all the code samples from the Zero to Mastery : Master the Coding Interview - Data Structures + Algorithms course by Andrei Neagoie, in Python.
Uzmamushtaque's Repositories
Uzmamushtaque/CSCI4962-Projects-ML-AI
This repo has the Lecture material for the course: projects in ML and AI
Uzmamushtaque/Projects-in-Machine-Learning-and-AI
Uzmamushtaque/CSCI-4967-Projects-in-ML-AI
This repo has the course material for Projects in ML/AI Course for Spring 2024
Uzmamushtaque/Instantutor
Peer-to-peer tutoring App
Uzmamushtaque/RecSysResearch
Uzmamushtaque/tensorflow-deep-learning
All course materials for the Zero to Mastery Deep Learning with TensorFlow course.
Uzmamushtaque/ZTM-DS-and-Algo-Python
Contains all the code samples from the Zero to Mastery : Master the Coding Interview - Data Structures + Algorithms course by Andrei Neagoie, in Python.
Uzmamushtaque/AB-Testing
A/B Testing — A complete guide to statistical testing
Uzmamushtaque/cookiecutter-data-science
A logical, reasonably standardized, but flexible project structure for doing and sharing data science work.
Uzmamushtaque/annotated_deep_learning_paper_implementations
🧑🏫 60 Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, sophia, ...), gans(cyclegan, stylegan2, ...), 🎮 reinforcement learning (ppo, dqn), capsnet, distillation, ... 🧠
Uzmamushtaque/Awesome-Diffusion-Models
A collection of resources and papers on Diffusion Models
Uzmamushtaque/copilot-docs
Documentation for GitHub Copilot
Uzmamushtaque/d2l-en
Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 200 universities.
Uzmamushtaque/fastai
The fastai deep learning library
Uzmamushtaque/FLASK-End-to-end-Zomato-Restaurant-Price-Prediction-and-Deployment
# **ABSTRACT** Main Objective: The main agenda of this project is: Perform extensive Exploratory Data Analysis(EDA) on the Zomato Dataset. Build an appropriate Machine Learning Model that will help various Zomato Restaurants to predict their respective Ratings based on certain features DEPLOY the Machine learning model via Flask that can be used to make live predictions of restaurants ratings A step by step guide is attached to this documnet as well as a video explanation of each concpet. Zomato is one of the best online food delivery apps which gives the users the ratings and the reviews on restaurants all over india.These ratings and the Reviews are considered as one of the most important deciding factors which determine how good a restaurant is. We will therefore use the real time Data set with variuos features a user would look into regarding a restaurant. We will be considering Banglore City in this analysis. Content The basic idea of analyzing the Zomato dataset is to get a fair idea about the factors affecting the establishment of different types of restaurant at different places in Bengaluru, aggregate rating of each restaurant, Bengaluru being one such city has more than 12,000 restaurants with restaurants serving dishes from all over the world. With each day new restaurants opening the industry has’nt been saturated yet and the demand is increasing day by day. Inspite of increasing demand it however has become difficult for new restaurants to compete with established restaurants. Most of them serving the same food. Bengaluru being an IT capital of India. Most of the people here are dependent mainly on the restaurant food as they don’t have time to cook for themselves. With such an overwhelming demand of restaurants it has therefore become important to study the demography of a location. What kind of a food is more popular in a locality. Do the entire locality loves vegetarian food. If yes then is that locality populated by a particular sect of people for eg. Jain, Marwaris, Gujaratis who are mostly vegetarian. These kind of analysis can be done using the data, by studying the factors such as • Location of the restaurant • Approx Price of food • Theme based restaurant or not • Which locality of that city serves that cuisines with maximum number of restaurants • The needs of people who are striving to get the best cuisine of the neighborhood • Is a particular neighborhood famous for its own kind of food. “Just so that you have a good meal the next time you step out” The data is accurate to that available on the zomato website until 15 March 2019. The data was scraped from Zomato in two phase. After going through the structure of the website I found that for each neighborhood there are 6-7 category of restaurants viz. Buffet, Cafes, Delivery, Desserts, Dine-out, Drinks & nightlife, Pubs and bars. Phase I, In Phase I of extraction only the URL, name and address of the restaurant were extracted which were visible on the front page. The URl's for each of the restaurants on the zomato were recorded in the csv file so that later the data can be extracted individually for each restaurant. This made the extraction process easier and reduced the extra load on my machine. The data for each neighborhood and each category can be found here Phase II, In Phase II the recorded data for each restaurant and each category was read and data for each restaurant was scraped individually. 15 variables were scraped in this phase. For each of the neighborhood and for each category their onlineorder, booktable, rate, votes, phone, location, resttype, dishliked, cuisines, approxcost(for two people), reviewslist, menu_item was extracted. See section 5 for more details about the variables. Acknowledgements The data scraped was entirely for educational purposes only. Note that I don’t claim any copyright for the data. All copyrights for the data is owned by Zomato Media Pvt. Ltd.. Source: Kaggle
Uzmamushtaque/GAR
This is the official code of GAR.
Uzmamushtaque/google-research
Google Research
Uzmamushtaque/instatutor
A P2P system works on the principle of sharing demand and supply across resources
Uzmamushtaque/learningsql-2875059
Uzmamushtaque/Linear-Attention-Mechanism
Attention mechanism
Uzmamushtaque/machine-learning-systems-design
A booklet on machine learning systems design with exercises
Uzmamushtaque/ML-with-Tensorflow
Uzmamushtaque/MLOps
A project-based course on the foundations of MLOps with a focus on intuition and application.
Uzmamushtaque/MLProjects
Uzmamushtaque/openvino
OpenVINO™ is an open-source toolkit for optimizing and deploying AI inference
Uzmamushtaque/pytorch_bert
Tutorial for how to build BERT from scratch
Uzmamushtaque/Rec_transform
Use of transformers for recommendations.
Uzmamushtaque/transformers
🤗 Transformers: State-of-the-art Natural Language Processing for Pytorch, TensorFlow, and JAX.
Uzmamushtaque/tutorials
AI-related tutorials. Access any of them for free → https://towardsai.net/editorial
Uzmamushtaque/wordcount-project