⚡ Harness the power of machine learning with our TensorFlow Dojo repository! Featuring a comprehensive set of free TensorFlow learning materials and a hands-on online environment, this is your training ground for building and deploying cutting-edge AI applications.
| Index | Name | Category | Description |
|---|---|---|---|
| 1 | Tensorflow for Deep Learning Research | University Courses | Learn the fundamentals of TensorFlow for deep learning research. Build models for tasks like word embeddings, translation, and optical character recognition. |
| 2 | Building a simple Generative Adversarial Network (GAN) using Tensorflow | Technical Tutorials | Hands-on introduction to building a simple Generative Adversarial Network (GAN) using TensorFlow. Understand the core concept, implement the model, and visualize the process. |
| 3 | Introduction to TensorFlow for AI, Machine Learning & Deep Learning | Video Courses | Gain hands-on experience in building neural networks, training them for computer vision, and understanding the use of convolutions to improve model performance. |
| 4 | Free and Open Machine Learning | Technical Tutorials | Discover the power of open-source machine learning with this comprehensive guide, covering key concepts, architecture, and FOSS tools for practical business applications. |
| 5 | Deep Learning Applications | University Courses | Explore the latest advancements in deep learning and its practical applications in computer vision, time series, security, NLP, and data generation. |
| 6 | Introduction to Artificial Intelligence | University Courses | Comprehensive AI course covering search, knowledge representation, reasoning, machine learning, and natural language processing. Hands-on experience with cutting-edge AI algorithms and applications. |
| 7 | Artificial Intelligence | University Courses | Comprehensive overview of AI principles, hands-on experience with algorithms, and insights into the ethical implications of Artificial Intelligence. |
| 8 | Deep Learning for Computer Vision | University Courses | Comprehensive introduction to deep learning techniques for computer vision tasks, including image classification, object detection, and segmentation. |
| 9 | Neural Networks: Zero to Hero | University Courses | Comprehensive video series by renowned expert Andrej Karpathy, covering neural network fundamentals, advanced techniques, and practical applications. |
| 10 | Neural Networks and Applications | University Courses | Comprehensive introduction to neural networks, covering architectures, algorithms, and real-world applications in image recognition, NLP, and predictive modeling. |
| 11 | Deep Learning | University Courses | Comprehensive overview of deep learning, covering fundamental concepts, architectures, and applications. Taught by Prof. Mitesh M. Khapra from IIT Madras. |
| 12 | Introduction to Deep Learning | University Courses | Dive into the fundamentals of deep learning with MIT's intensive bootcamp, covering cutting-edge topics in computer vision, natural language processing, and more. |
| 13 | Intro to Deep Learning & Generative Models | University Courses | Comprehensive course on deep learning fundamentals, generative models like VAEs and GANs, with hands-on tutorials using TensorFlow and PyTorch. |
| 14 | Deep Learning | University Courses | Comprehensive deep learning course from UC Berkeley covering neural networks, optimization, and real-world applications. Hands-on coding and experienced instructors. |
| 15 | Deep Learning | University Courses | Comprehensive introduction to deep learning, covering fundamental concepts, advanced topics, and hands-on exercises using popular frameworks like TensorFlow and PyTorch. |
| 16 | Deep Learning for Computer Vision | University Courses | Comprehensive course on deep learning for computer vision, covering CNN, RNN, GAN, and state-of-the-art models for image and video analysis. |
| 17 | Deep Learning: CS 182 | University Courses | Dive into the fundamentals of deep learning with this in-depth course, covering neural networks, optimization, and real-world applications in computer vision, NLP, and more. |
| 18 | Probabilistic Graphical Models | University Courses | Comprehensive introduction to probabilistic graphical models, covering theory, algorithms, and real-world applications in machine learning, computer vision, and natural language processing. |
| 19 | Foundations of Reinforcement Learning | University Courses | Comprehensive introduction to the fundamentals of reinforcement learning, including Markov decision processes, dynamic programming, and temporal-difference learning. |
| 20 | Reinforcement Learning | University Courses | Comprehensive course on reinforcement learning for AI, machine learning, and sequential decision-making problems. Covers core principles, algorithms, and real-world applications. |
| 21 | Introduction to Machine Learning for Coders | University Courses | Comprehensive and practical learning experience in deep learning, empowering learners to start training models within minutes and apply deep learning to real-world problems. |
| 22 | Deep Reinforcement Learning | University Courses | Explore the fundamentals of deep reinforcement learning, including algorithms, frameworks, and practical applications in areas like game playing, robotics, and resource management. |
| 23 | Reinforcement Learning | University Courses | Comprehensive course on reinforcement learning, covering fundamental concepts, advanced algorithms, and real-world applications in AI, robotics, and more. |
| 24 | Natural Language Processing | University Courses | Comprehensive online NLP course covering sentiment analysis, neural networks, word embeddings, and transformer language modeling. Includes hands-on coding assignments. |
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