[poster]

Sam Woods - Bionic GPTs, AI Agents | 587 MB

In this course, Sam Woods delves into the fascinating world of artificial intelligence and machine learning, focusing on the development of Bionic GPTs (Generative Pre-Trained Transformers) and AI agents. The course is designed to provide students with a comprehensive understanding of the latest advancements in AI and its applications.






Course Objectives:
- Understand the basics of artificial intelligence and machine learning
- Learn how to develop and train Bionic GPTs
- Explore the capabilities and limitations of AI agents
- Develop practical skills in AI programming and deployment


Course Outline:
Introduction to Artificial Intelligence and Machine Learning
- Overview of AI and its applications
- Fundamentals of machine learning: supervised and unsupervised learning, neural networks, and deep learning
- Introduction to Bionic GPTs and their role in AI


Bionic GPTs - Theory and Implementation
- In-depth exploration of Bionic GPTs: architecture, components, and training methods
- Hands-on training with Bionic GPTs using popular frameworks such as PyTorch and TensorFlow
- Case studies: applications of Bionic GPTs in natural language processing, computer vision, and speech recognition


AI Agents - Design and Development
- Introduction to AI agents: types, architectures, and characteristics
- Designing and developing AI agents using popular frameworks such as OpenCV and Robot Operating System (ROS)
- Case studies: applications of AI agents in robotics, autonomous vehicles, and game playing

Advanced Topics in AI
- Deep learning techniques: convolutional neural networks (CNNs), recurrent neural networks (RNNs), and long short-term memory (LSTM) networks
- Transfer learning and fine-tuning pre-trained models
- Exploring emerging trends in AI: Explainable AI, Adversarial Attacks, and Fairness in AI

Practical Applications of AI Agents
- Case studies: real-world applications of AI agents in industries such as healthcare, finance, and transportation
- Hands-on exercises: designing and implementing AI agents for specific tasks
- Challenges and limitations of AI agents in real-world scenarios


Future Directions in AI Research
- Emerging trends in AI research: multimodal learning, transfer learning, and reinforcement learning
- Exploring the potential applications of AI in areas such as space exploration, education, and social media
- Future directions for AI research: ethics, bias, and explainability

Homepage:

https://samueljwoods.com/

Screenshots


Link Download:

Download Via Rapidgator
https://rg.to/folder/7619444/SamWoodsBionicGPTsTraining.html

Download Via Uploadgig Free Download
https://uploadgig.com/file/download/3C04b48Ea49c4b8b/Sam.Woods.Bionic.GPTs.Training.02.19.part1.rar
https://uploadgig.com/file/download/5848Cbb83153ccbA/Sam.Woods.Bionic.GPTs.Training.02.19.part2.rar
https://uploadgig.com/file/download/16aa2Fb0aecda889/Sam.Woods.Bionic.GPTs.Training.02.19.part3.rar

Download Via Nitroflare
https://nitroflare.com/view/DF53D96F8845576/Sam.Woods.Bionic.GPTs.Training.02.19.part1.rar
https://nitroflare.com/view/341A2943A5CEE03/Sam.Woods.Bionic.GPTs.Training.02.19.part2.rar
https://nitroflare.com/view/C17D06D7AB7F6CC/Sam.Woods.Bionic.GPTs.Training.02.19.part3.rar

Links are Interchangeable - No Password - Single Extraction
Extract files with WinRar Latest !
Contact dead link: [email protected]