AI/ML Development Tools

Explore the essential tools and platforms to kickstart your Artificial Intelligence and Machine Learning journey.

Microsoft Azure Machine Learning

A cloud-based service that helps you train, deploy, and manage machine learning models at scale. Offers a visual designer and automated ML capabilities.

Cloud MLOps Python .NET
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Visual Studio Code

A lightweight yet powerful source code editor that supports extensions for virtually any programming language, including Python, R, and Julia, with excellent AI/ML integration.

IDE Python Jupyter Debugging
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TensorFlow

An open-source library developed by Google for numerical computation and large-scale machine learning. Widely used for deep learning.

Deep Learning Python Open Source GPU
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PyTorch

An open-source machine learning library based on the Torch library, used for applications such as computer vision and natural language processing, primarily developed by Meta AI.

Deep Learning Python Open Source Research
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Scikit-learn

A simple and efficient tools for predictive data analysis, built upon NumPy, SciPy, and Matplotlib. Offers a comprehensive suite of classification, regression, and clustering algorithms.

Machine Learning Python Scikit-learn Data Science
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Jupyter Notebook

An open-source web application that allows you to create and share documents containing live code, equations, visualizations, and narrative text. Ideal for data exploration and prototyping.

Interactive Data Science Python Web App
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ONNX Runtime

High performance inference engine for ONNX models. Allows you to run models trained in various frameworks on a wide range of hardware.

Inference ONNX Performance Cross-platform
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