Best of TensorFlow — 2023
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KDnuggets·3y
Free TensorFlow 2.0 Complete Course
Free TensorFlow 2.0 Complete Course is a tutorial for beginner python programmers interested in machine learning and neural networks using TensorFlow 2.0. The course covers fundamental concepts in ML & AI such as core learning algorithms, deep learning with neural networks, computer vision with convolutional neural networks, natural language processing with recurrent neural networks, and reinforcement learning. It requires basic knowledge of programming using Python and has a duration of 7 hours.
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Learn Machine Learning From These GitHub Repositories
Learn Machine Learning From These GitHub Repositories Kickstart your machine learning career with these curated GitHub repositories. The best of ML with Python repository has 910 open-source projects that are grouped into 34 categories. TensorFlow is one of the most popular machine learning frameworks out there and is vital to your skillset.
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Pointer·3y
mozilla/DeepSpeech: DeepSpeech is an open source embedded (offline, on-device) speech-to-text engine which can run in real time on devices ranging from a Raspberry Pi 4 to high power GPU servers.
DeepSpeech is an open source embedded (offline, on-device) speech-to-text engine. It can run in real time on devices ranging from a Raspberry Pi 4 to high power GPU servers. It uses a model trained by machine learning techniques based on Baidu's Deep Speech research paper.
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FlutterDevs·3y
Flutter: Building UI with Machine Learning capabilities
Machine Learning is a field of study that allows computers to learn without being explicitly programmed. Flutter is an open-source UI framework developed by Google for building cross-platform apps. It allows developers to create beautiful and performant apps for multiple platforms using a single codebase.
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freeCodeCamp·3y
Medical AI Models with TensorFlow – Tutorial
The freeCodeCamp.org YouTube course will teach you how to build and evaluate medical AI models with TensorFlow. Dr. Jason Adleberg is a radiologist in New York City and a skilled programmer. The course is structured into two parts, offering both theoretical knowledge and practical application.
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Python in Plain English·2y
The Best Python Packages For Developers To Use In 2023💥
This article discusses the best Python packages for developers to use in 2023. It highlights the reasons why Python is a popular choice, and provides information about various packages such as NumPy, TensorFlow, Django Packages, Seaborn, and more.
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Machine Learning News·3y
Best Image Annotation Tools in 2023
Image annotation is the process of labeling or categorizing an image with descriptive data that helps identify and classify objects, people, and situations included in the image. Markup Hero is an easy-to-use, flexible, and powerful image annotation tool ideal for real-time collaborative and visual communication.
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Developer.com·3y
7 Best Python Libraries for Machine Learning and AI
7 Best Python Libraries for Machine Learning and AI Artificial intelligence (AI) and machine learning (ML) are both popular fields in software development. This tutorial will highlight the best AI, ML and deep learning Python libraries that programmers, data scientists, and researchers can use to build intelligent applications and solve complex problems.
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How to Use TensorFlow for Deep Learning – Basics for Beginners
TensorFlow is a powerful library for building and training deep learning models. It can handle any type of data and feed it to machine learning models. TensorFlow supports a wide range of hardware and has a high-level API called Keras. In this article, you will learn about tensors, how to build and generate them, and perform basic operations using TensorFlow.
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LogRocket·2y
Using WebGPU to accelerate ML workloads in the browser
WebGPU is a cutting-edge technology that accelerates machine learning workloads in web applications by utilizing the local GPU. It allows developers to seamlessly integrate graphics and machine learning tasks, resulting in more interactive web experiences. WebGPU opens up exciting possibilities for web-based AI applications.
