Name: Md Junayed Hasan
Type: User
Company: National Subsea Centre
Bio: 🧠 Expert in AI, ML/DL, Computer Vision, Data Modelling | ⚡ Committed to Reliability, Safety, and Sustainable Energy
Twitter: drjunayedhasan
Location: Aberdeen
Md Junayed Hasan's Projects
A Keras framework for Adversarial Domain Adaptation
A repository with IPython notebooks of algorithms implemented in Python.
A Collection of application ideas which can be used to improve your coding skills.
The art of effective visualization of multi-dimensional data
Automatic Image Down-loader from Google.
A collection of AWESOME things about domian adaptation
:octocat: A curated awesome list of lists of interview questions. Feel free to contribute! :mortar_board:
Best transfer learning and domain adaptation resources (papers, tutorials, datasets, etc.)
Python implementations of the Boruta all-relevant feature selection method.
End-to-End DL project demo
Notebook demonstrating use of LIME to interpret a model of long-term relationship success
Resources for the Udemy Course - Azure Data Factory For Data Engineers - Project on Covid19
Intro to Digital Signal Processing and Compressive Sensing
CubiCasa5k floor plan dataset
A simple, high level, easy to use, open source Computer Vision library for Python.
A simple implementation of domain adversarial training with GAN loss in Keras
:bar_chart: Path to a free self-taught education in Data Science!
In this repository, I will try to contribute some of the fun projects which I did for the learning purpose of Data Science (DS) with Machine Learning (ML).
Multiclass bearing fault classification using features learned by a deep neural network.
Hosting all datasets collected from various sources
Tutorials on visualizing data using python packages like bokeh, plotly, seaborn and igraph
DDSP: Differentiable Digital Signal Processing
DEAP Dataset Analysis Code
Deep Embedding Clustering in Keras
Deep Learning Specialization by Andrew Ng on Coursera - My Completed Coursework Repo - All 5 Courses
Drench yourself in Deep Learning, Reinforcement Learning, Machine Learning, Computer Vision, and NLP by learning from these exciting lectures!!