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Tesla AI-DL-ML-LLM related GitHub Repositories
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For the top 15 GitHub repos, ask for 10 paragraphs. e.g. Amazon SageMaker Features, Amazon SageMaker Alternatives, Amazon SageMaker Security, , Amazon SageMaker DevOps
Deep Learning with Google Colab: Utilizing Tesla GPUs
The repository “Deep Learning with Google Colab” demonstrates the application of deep learning models using Google Colaboratory, leveraging free access to Tesla K80, Tesla T4, and Tesla P100 GPUs. It includes implementations of models such as YOLOv3, YOLOv4, and DeOldify for tasks like object detection and image colorization, showcasing the integration of these GPUs in deep learning workflows.
DeepTesla: End-to-End Learning from Autopilot Data
The “DeepTesla” project focuses on end-to-end learning from Tesla Autopilot driving data. It utilizes deep learning techniques to predict steering angles based on front-facing camera images, aiming to replicate human driving behavior. This approach highlights the potential of deep learning in autonomous driving applications.
Tesla Simulator: JavaScript-Based Deep Learning
The “Tesla Simulator” is a JavaScript framework for deep learning and reinforcement learning in the browser. It features a 2D self-driving car simulation, allowing users to visualize and experiment with neural network capabilities directly in their web browsers. This project demonstrates the accessibility of deep learning concepts through browser-based simulations.
Deep-Tesla: Learning from Human and Autopilot Driving
The “Deep-Tesla” repository explores end-to-end learning from both human and Autopilot driving data. It employs deep learning models to predict vehicle control commands from camera images, contributing to the development of autonomous driving systems by learning from diverse driving behaviors.
Liquid Neural Networks in Stock Market Prediction
This repository hosts a stock market prediction model for companies like Tesla and Apple using Liquid Neural Networks. It showcases data-driven forecasting techniques, feature engineering, and machine learning to enhance the accuracy of financial predictions, applying advanced neural network architectures to time-series data.
https://github.com/HusseinJammal/Liquid-Neural-Networks-in-Stock-Market-Prediction
Tesla Sales Prediction Using Machine Learning
The “Tesla Sales Prediction” project utilizes machine learning and deep learning techniques to forecast sales figures. It incorporates data such as monthly sales, pricing, number of charging stations, and GDP metrics to build robust predictive models, aiding in strategic planning and market analysis.
PyTorch: Deep Learning Framework
PyTorch, developed by Meta AI and released in 2016, is an open-source machine learning library based on the Torch library. It is widely used for applications such as computer vision and natural language processing. Notably, Tesla Autopilot utilizes PyTorch for its deep learning models, highlighting the framework's applicability in autonomous driving systems.
sunnypilot: Open Source Driver Assistance System
The “sunnypilot” project is an open-source driver assistance system compatible with over 290 car makes and models, including those from Tesla. It modifies behaviors of driving assist engagements and complies with comma.ai's safety rules, offering a unique driving experience and contributing to the development of autonomous driving technologies.
Autopilot: Self-Driving Car Module for Humans
The “Autopilot” repository provides a simple self-driving car module inspired by NVIDIA's end-to-end learning for self-driving cars. It focuses on predicting steering angles from camera images using deep learning models, serving as an educational tool for understanding autonomous driving concepts.
TeslaPy: Python Module for Tesla Owner API
“TeslaPy” is a Python module that interfaces with the Tesla Motors Owner API. It allows users to monitor and control their Tesla vehicles programmatically, facilitating the integration of vehicle data into custom applications and contributing to the development of connected car technologies.
https://github.com/tdorssers/TeslaPy
Tesla's Open-Source Contributions: A Hub of Innovation
Tesla, Inc. maintains an active presence on GitHub, hosting a variety of repositories that reflect its commitment to open-source development. These repositories encompass projects ranging from vehicle software to development tools, showcasing Tesla's dedication to technological advancement and community collaboration.
Fleet Telemetry: Enhancing Vehicle Data Analysis
The fleet-telemetry repository, updated as recently as November 2024, is designed to facilitate the collection and analysis of vehicle data. This tool aids in monitoring fleet performance, diagnosing issues, and optimizing vehicle operations, contributing to improved efficiency and reliability.
Vehicle Command: Streamlining Vehicle Interactions
The vehicle-command repository, last updated in November 2024, provides tools for interacting with vehicle systems. It enables developers to send commands and retrieve data from vehicles, supporting the development of applications that enhance user experience and vehicle functionality.
Light Show: Creating Custom Vehicle Light Displays
The light-show repository, updated in September 2024, allows users to create and customize light shows for their vehicles. This feature enables owners to program unique light sequences, adding a personalized touch to their vehicles and enhancing the ownership experience.
React Native Camera Kit: High-Performance Camera Library
The react-native-camera-kit repository, updated in November 2024, offers a high-performance, easy-to-use camera library for React Native applications. It simplifies the integration of camera functionalities into mobile apps, providing developers with robust tools for building feature-rich applications.
Informed: Building Powerful Forms in React
The informed repository, updated in November 2024, is a lightweight framework and utility for building powerful forms in React applications. It streamlines form creation and management, enhancing the efficiency of developing interactive web applications.
Fixed Containers: Optimizing C++ Data Structures
The fixed-containers repository, updated in November 2024, focuses on fixed-size containers in C++. It provides data structures optimized for performance and memory usage, beneficial for applications requiring deterministic behavior and resource efficiency.
Ansible Puller: Scalable Configuration Management
The ansible_puller repository, updated in November 2024, is an Ansible daemon designed for massively scalable configuration management. It facilitates the automation of system configurations across large infrastructures, improving consistency and deployment speed.
TTPOE: Enhancing Network Protocols
The ttpoe repository, updated in November 2024, focuses on network protocol enhancements. It aims to improve the efficiency and reliability of data transmission, contributing to more robust communication systems.
Zephyr: Scalable Real-Time Operating System
The zephyr repository, updated in November 2024, is the primary Git repository for the Zephyr Project. Zephyr is a new generation, scalable, optimized, secure real-time operating system (RTOS) for multiple hardware architectures, supporting the development of embedded systems.
https://github.com/teslamotors/zephyr