Amitash Nanda's repositories
Particle-Filter-and-Visual-Inertial-Simultaneous-Localization-and-Mapping
Implemented visual-inertial SLAM using an extended Kalman filter using IMU and stereo camera measurements from an autonomous car. First performed IMU localization via EKF prediction, then landmark mapping via EKF update.
Color-Classification-and-Recycling-Bin-Detection
Developed a color classification model and drawing the concept from later to detect recycle bins using Gaussian Discriminant Analysis
model-compression-technique-for-on-device-learning
Researching on developing more sophisticated pruning and quantization technique for characterization of biases for the compressed model.
3d-radnet
Transfer learning with medical images
OrgaTuring-Accelerating-Organoid-Discovery-with-visual-AI
OrgaTuring is a novel deep-learning approach to investigating organoids and designing a real-time accurate medical device. The CNN-based interpretable deep-learning model facilitates the real-time location, quantification, tracking, and classification of organoids from 2D and 3D images. This research will serve as a stepping stone to creating smart point-of-care devices equipped with mobile healthcare.
Robot_Testing_Framework
Robot Testing Platform to test robots in real world scenario
TinyML-with-STM32-NUCLEO-L432KC
This repository shows the design of a light weight CNN based deep-learning algorithm that discriminates life-threatening ventricular arrhythmias (reason for sudden cardiac death) from IEGM recordings and deployed on STM32 NUCLEO-L432KC
chart-gpt
AI tool to build charts based on text input
FL-Reading-List
Federated Learning Reading List and Notes
handson-ml2
A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.
Impact-of-Feature-Correlation-on-Feature-Importance-using-SHAP
Detail Analysis to know if Shapley interaction values capture information about feature correlations and if the interaction values can be used to obtain a more accurate feature ranking.
IntelNeuromorphicDNSChallenge
Intel Neuromorphic DNS Challenge
Interpretability-in-ChexNet
Implemented CNN-based Deep-Learning model(s) to detect pneumonia from chest X-rays, also Incorporated model interpretability using Sample Handling and Analysis Plan (SHAP). Then used the above metrics to quantify training data based on quality for better model performance and reliability.
ML-Course-Notes
🎓 Sharing course notes on all topics related to machine learning, NLP, and AI.
ml-study-plan
The Ultimate FREE Machine Learning Study Plan
python_for_microscopists
https://www.youtube.com/channel/UC34rW-HtPJulxr5wp2Xa04w?sub_confirmation=1
shap-hypetune
A python package for simultaneous Hyperparameters Tuning and Features Selection for Gradient Boosting Models.
t81_558_deep_learning
Washington University (in St. Louis) Course T81-558: Applications of Deep Neural Networks
TensorFlow-Examples
TensorFlow Tutorial and Examples for Beginners (support TF v1 & v2)
Ultrasound-US-Modulations
Ultrasound (US) Modulations: Effects of Changing US Transducer Probe & Reconstruction Parameters on Sound Intensity and Image Quality