Iman Khazrak's Projects
Upload your fasta file and receive its fastq format.
Using this tool you can convert your work in Colab to HTML and submit it as a report.
📚 Papers & articles of companies sharing their work on applied data science & machine learning.
Curated list of Machine Learning, NLP, Vision, Recommender Systems Project Ideas
TensorFlow code and pre-trained models for BERT
BERT-related papers
Best Practices, code samples, and documentation for Computer Vision.
Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 300 universities from 55 countries including Stanford, MIT, Harvard, and Cambridge.
Denoising Diffusion Probabilistic Models: without improvement
Release for Improved Denoising Diffusion Probabilistic Models
Implementation of Denoising Diffusion Probabilistic Model in Pytorch
Visuakization using D3 JS
Get familiar with various techniques to handle the imbalanced class.
# Bayesian Optimization In this example a bayesian framework is defined to tune hyperparameter of a CNN using hyperopt library developed https://github.com/hyperopt Bayesian optimization is a seuential model-based approach to solving problems. In particular, we prescribe a prior belief over the possible objective functions and then sequentially refine this model as data are observed via our updated beliefs-given data-on the likely ojective function we are optimizing. https://www.cs.ox.ac.uk/people/nando.defreitas/publications/BayesOptLoop.pdf This blog summarises bayesian optimization very thoroughly. https://medium.com/vantageai/bringing-back-the-time-spent-on-hyperparameter-tuning-with-bayesian-optimisation-2e21a3198afb The CNN is used to model fashion MNIST dataset.
Deep domain adaptation networks (DDAN) library for Python with TensorFlow.
In this repository the code that ensemble different REFINED approaches is provided.
An Introduction to Statistical Learning (James, Witten, Hastie, Tibshirani, 2013): Python code
🧑🏫 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, ... 🧠
Becoming better at data science every day
matplotlib: plotting with Python
This repository explains machine learning concepts
Examples of Message Passing Interface in Python using MPI4PY
We introduce a novel approach for parameter generation, named neural network diffusion (\textbf{p-diff}, p stands for parameter), which employs a standard latent diffusion model to synthesize a new set of parameters
✍️ A carefully curated list of NLP paper summaries
100 numpy exercises (with solutions)
Interactive Car Data Visualization
React
Typescript
Django
Laravel
Facebook
Microsoft
Google
Alibaba
D3
Tencent