Karamya
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docTR (Document Text Recognition) - a seamless, high-performing & accessible library for OCR-related tasks powered by Deep Learning.
A flexible package for multimodal-deep-learning to combine tabular data with text and images using Wide and Deep models in Pytorch
Host repository for the "Reproducible Deep Learning" PhD course
1st place solution for the Kaggle PANDA Challenge
Utilities for ML, AI, and kaggle competitions
Panel: The powerful data exploration & web app framework for Python
Machine Learning From Scratch. Bare bones NumPy implementations of machine learning models and algorithms with a focus on accessibility. Aims to cover everything from linear regression to deep lear…
Memorizing Normality to Detect Anomaly: Memory-augmented Deep Autoencoder for Unsupervised Anomaly Detection (MemAE)
Tutorial for International Summer School on Deep Learning, 2019
A collection of various deep learning architectures, models, and tips
This is a repository which contains all my work related Machine Learning, AI and Data Science. This includes my graduate projects, machine learning competition codes, algorithm implementations and …
YSDA course in Natural Language Processing
Unsupervised anomaly detection with generative model, keras implementation
An opinionated list of awesome Python frameworks, libraries, software and resources.
Lightweight, Python library for fast and reproducible experimentation 🔬
Repository for "Introduction to Artificial Neural Networks and Deep Learning: A Practical Guide with Applications in Python"
Easy-to-run example notebooks for Dask
1 Line of code data quality profiling & exploratory data analysis for Pandas and Spark DataFrames.
Deep Reinforcement Learning Demos
Chatbot which talks to the user about available products
subtitles and other youtube statistics are collected in a relational database over APIs and NLP methods used to find text similarity to published works. A Flask frontend runs locally, serving a res…
An open source framework for seq2seq models in PyTorch.
🌎 machine learning tutorials (mainly in Python3)