1.TensorFlow:· Usage: TensorFlow is an open-source machine learning framework developed by Google. It's widely used for building and training deep neural networks for various tasks, including image and speech recognition, natural language processing, and reinforcement learning.
By HITESH ABROL
SEP 7,2023
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2. PyTorch:· Usage: PyTorch is another popular open-source deep learning framework, primarily developed by Facebook's AI Research lab. It's favored by researchers and practitioners for its dynamic computation graph and ease of use in building neural networks for tasks like image classification, language modeling, and more.
By HITESH ABROL
SEP 7,2023
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3. scikit-learn:· Usage: scikit-learn is a Python library that provides a wide range of tools for machine learning and data mining. It's used for tasks such as classification, regression, clustering, and dimensionality reduction. It's a great choice for traditional machine learning algorithms.
By HITESH ABROL
SEP 7,2023
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4. Keras:· Usage: Keras is an open-source neural network library written in Python. It serves as a high-level API that can run on top of other deep learning frameworks like TensorFlow. Keras simplifies the process of building and training neural networks, making it accessible for beginners and researchers alike.
By HITESH ABROL
SEP 7,2023
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5. IBM Watson:· Usage: IBM Watson is a suite of AI and machine learning tools and services offered by IBM. It can be used for various applications, including natural language processing, computer vision, chatbots, and data analysis. Watson offers pre-trained models and APIs for integration into various applications.
By HITESH ABROL
SEP 7,2023
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6. OpenAI GPT-3 (and successors):· Usage: GPT-3, developed by OpenAI, is a powerful language model known for its natural language understanding and generation capabilities. Developers and businesses use GPT-3 and similar models for tasks such as chatbots, content generation, text summarization, and language translation.
By HITESH ABROL
SEP 7,2023
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7. Microsoft Azure Cognitive Services:· Usage: Microsoft Azure Cognitive Services provides a range of AI services and APIs for various applications. These services include computer vision for image analysis, speech recognition, language understanding, and more. Developers can use these services to add AI capabilities to their applications and services.