udacity-nanodegree

🎓 List of Udacity Nanodegree programs with links to the free courses in their curricula

Udacity Nanodegree and Course Downloader

Projects done in the Data Engineering Nanodegree by Udacity.com

My personal notes, presentations, and notebooks on everything Deep Learning.

All projects and lecture notes of the Udacity Machine Learning Engineer Nanodegree.

Data Structures & Algorithms Nanodegree Program from Udacity

Course projects for the Sensor Fusion Nanodegree program on Udacity.

➿ 💡 My Udacity projects that I have made to improve my skills and complete my nanodegree. Please don't use it to copy the projects. Submit the PR if you want something to be added to this repository.

Introduction to Computer Vision (Udacity Course)

An implementation of the Deep Knowledge Tracing (DKT) using Tensorflow 2.0

Tutorials and my solutions to the Udacity NLP Nanodegree

List of iOS Udacity Nanodegree programs with links to the free courses in their curricula

Final Project of the Udacity AI Programming with Python Nanodegree

Udacity Full Stack Web Developer Nanodegree program (FSND) course materials

The road so far on Udacity Blockchain Developer Nanodegree

🎓 Udacity Nano Degree Android Projects. All Needed projects you can check out my work here. Submitted and accepted projects.

A repo for the live coding portion of my full stack Javascript Developer Nanodegree sessions

This repo includes all the projects I have finished in the Udacity Nanodegree programs

Learn to detect obstacles in lidar point clouds through clustering and segmentation, apply thresholds and filters to radar data in order to accurately track objects, and augment your perception by projecting camera images into three dimensions and fusing these projections with other sensor data. Combine this sensor data with Kalman filters to perceive the world around a vehicle and track objects over time.

The course is contained knowledge that are useful to work on deep learning as an engineer. Simple neural networks & training, CNN, Autoencoders and feature extraction, Transfer learning, RNN, LSTM, NLP, Data augmentation, GANs, Hyperparameter tuning, Model deployment and serving are included in the course.