Top 100 AI tools, programming Language and framework

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Here are the top 100 AI tools, programming languages, and frameworks used in the industry:

AI Tools:

  1. TensorFlow: TensorFlow is an open-source platform developed by Google for building and training machine learning models.
  2. PyTorch: PyTorch is an open-source machine learning library that is used for developing deep learning models.
  3. Keras: Keras is a high-level neural network API written in Python and can be run on top of TensorFlow, Theano, or CNTK.
  4. Caffe: Caffe is an open-source deep learning framework developed by the Berkeley Vision and Learning Center (BVLC).
  5. Apache Mahout: Apache Mahout is an open-source project that provides scalable machine learning algorithms for clustering, classification, and collaborative filtering.
  6. H2O.ai: H2O.ai is an open-source platform for building and deploying machine learning models in enterprises.
  7. Microsoft Cognitive Toolkit: The Microsoft Cognitive Toolkit is an open-source deep learning framework that provides a set of tools for building and training machine learning models.
  8. Scikit-learn: Scikit-learn is a Python library that provides a range of supervised and unsupervised learning algorithms for data analysis.
  9. Amazon SageMaker: Amazon SageMaker is a cloud-based machine learning platform that provides tools for building, training, and deploying machine learning models at scale.
  10. IBM Watson Studio: IBM Watson Studio is a cloud-based platform for building, deploying, and managing machine learning models.
  11. BigDL: BigDL is an open-source distributed deep learning library for Apache Spark.
  12. MLlib: MLlib is a machine learning library built on top of Apache Spark for distributed machine learning.
  13. Deeplearning4j: Deeplearning4j is an open-source deep learning library for the Java Virtual Machine (JVM).
  14. Theano: Theano is a Python library that allows developers to define, optimize, and evaluate mathematical expressions involving multi-dimensional arrays efficiently.
  15. MXNet: MXNet is an open-source deep learning framework that supports multiple programming languages and allows developers to run models on a range of devices, including CPUs, GPUs, and cloud platforms.
  16. CNTK: CNTK is an open-source deep learning toolkit developed by Microsoft Research for building deep neural networks.
  17. PyBrain: PyBrain is an open-source machine learning library for Python that provides tools for building and training neural networks.
  18. RapidMiner: RapidMiner is a machine learning and data mining platform that provides a range of tools for building and deploying predictive models.
  19. Weka: Weka is an open-source machine learning platform that provides a range of tools for data mining, predictive modeling, and visualization.
  20. Orange: Orange is an open-source data analysis and visualization tool that provides a range of tools for data mining, machine learning, and predictive modeling.
  21. Apache Beam: Apache Beam is an open-source platform for building batch and streaming data processing pipelines.
  22. DataRobot: DataRobot is a cloud-based platform for building and deploying machine learning models at scale.
  23. KNIME Analytics Platform: KNIME Analytics Platform is an open-source platform for data analytics, machine learning, and predictive modeling.
  24. OpenCV: OpenCV is an open-source computer vision library that provides tools for image and video processing.
  25. Apache MXNet: Apache MXNet is an open-source deep learning framework that supports multiple programming languages and allows developers to run models on a range of devices, including CPUs, GPUs, and cloud platforms.
  26. MATLAB: MATLAB is a high-level programming language that is widely used in engineering and scientific applications, including machine learning.
  27. Orange3: Orange3 is an open-source platform for data analytics, machine learning, and predictive modeling
  1. Google Cloud Machine Learning Engine: Google Cloud Machine Learning Engine is a cloud-based platform for building and deploying machine learning models at scale.
  2. Apache Flink: Apache Flink is an open-source platform for real-time stream processing and batch processing.
  3. TensorFlow.js: TensorFlow.js is an open-source library for building and training machine learning models in JavaScript.
  4. Microsoft Azure Machine Learning: Microsoft Azure Machine Learning is a cloud-based platform for building and deploying machine learning models at scale.
  5. AllenNLP: AllenNLP is an open-source platform for natural language processing (NLP) that provides a range of tools for building and training NLP models.
  6. Pyro: Pyro is an open-source probabilistic programming language for building and training probabilistic models.
  7. Turi Create: Turi Create is an open-source platform for building and training machine learning models in Python.
  8. Apache NiFi: Apache NiFi is an open-source platform for data integration, including data processing, transformation, and routing.
  9. Apache Zeppelin: Apache Zeppelin is an open-source platform for data analytics and visualization that supports multiple programming languages, including Python, R, and SQL.
  10. Kibana: Kibana is an open-source platform for data visualization that is used with Elasticsearch for data exploration and analysis.
  11. TensorFlow Extended (TFX): TensorFlow Extended is an end-to-end machine learning platform for building and deploying production-ready machine learning models.
  12. Databricks: Databricks is a cloud-based platform for data engineering, data science, and machine learning that provides tools for building and deploying machine learning models at scale.
  13. KNIME Server: KNIME Server is a cloud-based platform for data analytics, machine learning, and predictive modeling.
  14. Deep Cognition: Deep Cognition is a cloud-based platform for building and deploying machine learning models that provides a range of tools for data processing, model training, and deployment.
  15. Dataiku DSS: Dataiku DSS is a collaborative platform for building and deploying machine learning models that provides a range of tools for data processing, modeling, and deployment.
  16. MLflow: MLflow is an open-source platform for managing machine learning experiments and deploying machine learning models at scale.
  17. AllenSDK: AllenSDK is an open-source platform for neuroscience research that provides a range of tools for analyzing and visualizing brain data.
  18. CatBoost: CatBoost is an open-source machine learning library that provides tools for building and training gradient boosting models.
  19. LightGBM: LightGBM is an open-source machine learning library that provides tools for building and training gradient boosting models.
  20. XGBoost: XGBoost is an open-source machine learning library that provides tools for building and training gradient boosting models.
  21. Prophet: Prophet is an open-source platform for time series forecasting that provides a range of tools for analyzing and predicting time series data.
  22. OpenAI Gym: OpenAI Gym is an open-source platform for developing and comparing reinforcement learning algorithms.
  23. Ray: Ray is an open-source platform for distributed computing and machine learning that provides a range of tools for building and deploying machine learning models at scale.
  24. PyTorch Lightning: PyTorch Lightning is an open-source platform for building and training PyTorch models.
  25. Hugging Face Transformers: Hugging Face Transformers is an open-source platform for natural language processing that provides a range of tools for building and training NLP models.
  26. GPT-3: GPT-3 is an artificial intelligence language model developed by OpenAI that provides a range of tools for natural language processing.
  27. OpenAI Codex

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