Name: Hashir Ahmad
Type: User
Company: Max Planck Institute for Biological Intelligence
Bio: Building connectomics toolkits and pipelines at @StructuralNeurobiologyLab
Location: Munich, Germany
Hashir Ahmad's Projects
A list of 99 machine learning projects for anyone interested to learn from coding and building projects
:memo: An awesome Data Science repository to learn and apply for real world problems.
Case Study for Data Analysis & Visualization in R
A smart IntelliJ plugin providing real time feedback on a user's stress levels while coding. Made by the students of Department of Informatics at Technical University of Munich in hackaTUM 2019
Toturial coming with "data science roadmap" graphe.
R's data.table package extends data.frame:
A Lightweight Face Recognition and Facial Attribute Analysis (Age, Gender, Emotion and Race) Library for Python
Deep Learning Nanodegree Project 2 | Dog Breed Classifier
Real-time implementation of emotion recognition using PyTorch and OpenCV
Real-time implementation of facial keypoints detection using PyTorch and OpenCV
Deep Learning Nanodegree Project 4 | Generate Faces
Deep Learning Nanodegree Project 3 | Generate TV Scripts
Profile readme
Published with Jekyll, Lanyon and GitHub Pages.
Fastest unstructured dataset management for TensorFlow/PyTorch. Stream data real-time & version-control it. http://activeloop.ai
Information Retrieval in High Dimensional Data | Course Assignments
A collection of practical examples, interactive tutorials, and code samples in and around LangChain.
A content-first, sliding sidebar theme for Jekyll.
https://huyenchip.com/ml-interviews-book/
WebGL-based viewer for volumetric data
Repository for OpenCV's extra modules
Deep Learning Nanodegree Project 1 | Predicting Bike Sharing Patterns
Python3 binding to mRMR Feature Selection algorithm (currently not maintained)
All Algorithms implemented in Python
Tensors and Dynamic neural networks in Python with strong GPU acceleration
Geometric Deep Learning Extension Library for PyTorch
Code and associated files for the deploying ML models within AWS SageMaker