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            An end-to-end platform for machine learning
            Install TensorFlow

            Get started with TensorFlow

              TensorFlow makes it easy to create ML models that can run in any environment. Learn how to use the intuitive APIs through interactive code samples.

              View tutorials
              import tensorflow as tf
              mnist = tf.keras.datasets.mnist
              
              (x_train, y_train),(x_test, y_test) = mnist.load_data()
              x_train, x_test = x_train / 255.0, x_test / 255.0
              
              model = tf.keras.models.Sequential([
                tf.keras.layers.Flatten(input_shape=(28, 28)),
                tf.keras.layers.Dense(128, activation='relu'),
                tf.keras.layers.Dropout(0.2),
                tf.keras.layers.Dense(10, activation='softmax')
              ])
              
              model.compile(optimizer='adam',
                loss='sparse_categorical_crossentropy',
                metrics=['accuracy'])
              
              model.fit(x_train, y_train, epochs=5)
              model.evaluate(x_test, y_test)
                Run quickstart

          Solve real-world problems with ML

            Explore examples of how TensorFlow is used to advance research and build AI-powered applications.

                TENSORFLOW.JS
            Catch up on the latest from the Web AI Summit

              Explore the latest advancements in running models client-side with speakers from Chrome, MediaPipe, Intel, Hugging Face, Microsoft, LangChain, and more.

              Watch now
            close
                TensorFlow GNN
            Analyze relational data using graph neural networks

              GNNs can process complex relationships between objects, making them a powerful technique for traffic forecasting, medical discovery, and more.

              Learn about TF GNN
                TensorFlow Agents
            Build recommendation systems with reinforcement learning

              Learn how Spotify uses the TensorFlow ecosystem to design an extendable offline simulator and train RL Agents to generate playlists.

              Read the blog

        What's new in TensorFlow

          Read the latest announcements from the TensorFlow team and community.

            Explore the ecosystem

              Discover production-tested tools to accelerate modeling, deployment, and other workflows.

              * Library

                TensorFlow.js

                Train and run models directly in the browser using JavaScript or Node.js.

              * Library

                LiteRT

                Deploy ML on mobile and edge devices such as Android, iOS, Raspberry Pi, and Edge TPU.

              * API

                tf.data

                Preprocess data and create input pipelines for ML models.

              * Library

                TFX

                Create production ML pipelines and implement MLOps best practices.

              * API

                tf.keras

                Create ML models with TensorFlow's high-level API.

              * Resource

                Kaggle Models

                Find pre-trained models ready for fine-tuning and deployment.

              * Resource

                TensorFlow Datasets

                Browse the collection of standard datasets for initial training and validation.

              * Tool

                TensorBoard

                Visualize and track development of ML models.

                  ML models & datasets

                  Pretrained models and ready-to-use datasets for image, text, audio, and video use cases.

                  Libraries & extensions

                  Packages for domain-specific applications and APIs for languages other than Python.

                  Developer tools

                  Tools to evaluate models, optimize performance, and productionize ML workflows.

              Join the community

              Collaborate, find support, and share your projects by joining interest groups or attending developer events.

              Get involved
              Learn ML

              New to machine learning? Begin with TensorFlow's curated curriculums or browse the resource library of books, online courses, and videos.

              Explore resources

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