• Google Colaboratory:
  • Features: Cloud-based Jupyter notebook environment with free GPU and TPU access. Supports popular AI frameworks like Tensor Flow and PyTorch. Allows collaboration and sharing of notebooks.

• Microsoft Azure Notebooks:
  • Features: Cloud-based Jupyter notebooks with Python support. Integration with Azure services. Provides free compute resources for experimentation and development.

• IBM Watson Studio Lite:
  • Features: Free version of the Watson Studio platform. Enables the creation and deployment of machine learning models. Collaboration capabilities and access to various AI services.

• H2O.ai Driverless AI Community Edition:
  • Features: Free community edition of H2O.ai’s automated machine learning platform. Offers advanced AI capabilities for feature engineering, model training, and deployment.

• DataRobot Community Edition:
  • Features: Free version of DataRobot’s automated machine learning platform. User-friendly interface for building and deploying machine learning models. Collaboration and sharing features.

• TensorFlow:
  • Features: Open-source machine learning framework by Google. Offers extensive tools and libraries for building and deploying AI models. Supports deep learning and neural networks.

• PyTorch:
  • Features: Open-source machine learning framework known for its flexibility and dynamic nature. Popular among researchers and practitioners. Provides tools for building deep learning models.

• OpenAI GPT-3 Playground:
  • Features: Free playground for experimenting with OpenAI’s language generation model, GPT-3. Allows interactive text generation and exploration of the model’s capabilities.

• Fast.ai:
  • Features: Deep learning library built on top of PyTorch. Offers high-level abstractions and simplifications for training deep learning models. Provides pre-trained models and datasets.

• DeepMind Lab:

• Features: 3D virtual environment developed by DeepMind for AI research. Allows testing and evaluation of reinforcement learning algorithms. Provides tools for creating custom environments.

These platforms offer a range of features and capabilities to support AI development, from Jupyter notebook environments and collaboration features to advanced automated Machine Learning and deep learning frameworks. They provide an opportunity to explore and experiment with AI without any financial cost.

The post Here are some free AI platforms you can use in 2022/2023, along with their features appeared first on mikemmtech.