# June 2023

TensorFlow Newsletter June 2023


Explore new tools, use LLMs in real-world applications, and more

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| |---| | |---| | [![](https://gstatic.com/growthlab/api/5bVWsgT8ttKvlVaE5gRkjgAiBv9mwnyIQkgpcp0q.png)](https://www.tensorflow.org/subscribe/2023/06#) | | | |---| | |---| | |---| | Learn how Keras makes deep learning easy | | | |---| | |---| | |---| | |---| | Explore the components of the Keras API, which provides an approachable interface for solving machine learning problems with TensorFlow. | | | |---| | [View developer guide](https://www.tensorflow.org/guide/keras?utm_source=email&utm_medium=newsletter&utm_campaign=tensorflow-june23) | | | | | | |---| |   | | | |---| | |---| | |---| | |---| | |---| | |---| | |---| | [![](https://gstatic.com/growthlab/api/qH9Xn4sAL4b8qjwN5TXhiMQQ6shmjGsT4NCMSfrT.gif)](https://www.tensorflow.org/lite/examples/auto_complete/overview?utm_source=email&utm_medium=newsletter&utm_campaign=tensorflow-june23) | | Create an autocomplete Android app with KerasNLP and TensorFlow Lite | | Large language models (LLMs) are trained to generate text based on large datasets. Learn how to load a KerasNLP model, optimize it with quantization techniques, and deploy it to an Android demo app that can run any compatible TFLite LLMs. | | |---| | |---| | |---| | |---|---| | |---| | [View example](https://www.tensorflow.org/lite/examples/auto_complete/overview?utm_source=email&utm_medium=newsletter&utm_campaign=tensorflow-june23) | | |---| | [![](https://www.gstatic.com/growthlab/api/Obmfy5bg9fJotE3zdZDXu4HiZx1oT3KnprcfW3ED.png)](https://www.tensorflow.org/lite/examples/auto_complete/overview?utm_source=email&utm_medium=newsletter&utm_campaign=tensorflow-june23) | | | | | | | | | | | |---| | |---| | |---| | |---| | [![](https://gstatic.com/growthlab/api/MCUoKvxdQiPTd7xglXknrLVKsqNOEqJx5EI4BOrq.png)](https://visualblocks.withgoogle.com/?utm_source=email&utm_medium=newsletter&utm_campaign=tensorflow-june23) | | Bring ML ideas to life using Visual Blocks | | Visual Blocks is a new graphical programming framework for rapid prototyping and experimentation. Use powerful machine learning building blocks like PaLM 2, iterate within a visual interface, and easily deploy. | | |---| | |---| | |---| | |---|---| | |---| | [Try Visual Blocks](https://visualblocks.withgoogle.com/?utm_source=email&utm_medium=newsletter&utm_campaign=tensorflow-june23) | | |---| | [![](https://www.gstatic.com/growthlab/api/Obmfy5bg9fJotE3zdZDXu4HiZx1oT3KnprcfW3ED.png)](https://visualblocks.withgoogle.com/?utm_source=email&utm_medium=newsletter&utm_campaign=tensorflow-june23) | | | | | | | | | | | |---| | |---| | |---| | |---| | [![](https://gstatic.com/growthlab/api/8Uh70Kx6sclpnHLUp9IsJ1Fc6B6ee4Zr1YvjFswn.png)](https://blog.tensorflow.org/2023/06/on-device-fetal-ultrasound-assessment-with-tensorflow-lite.html?utm_source=email&utm_medium=newsletter&utm_campaign=tensorflow-june23) | | Expanding access to ultrasound technology with TensorFlow Lite | | Read how Google's Health AI team is working to expand global access to maternal healthcare by building a mobile-optimized fetal ultrasound system using **TensorFlow Lite** for on-device inference. | | |---| | |---| | |---| | |---|---| | |---| | [Read the blog](https://blog.tensorflow.org/2023/06/on-device-fetal-ultrasound-assessment-with-tensorflow-lite.html?utm_source=email&utm_medium=newsletter&utm_campaign=tensorflow-june23) | | |---| | [![](https://www.gstatic.com/growthlab/api/Obmfy5bg9fJotE3zdZDXu4HiZx1oT3KnprcfW3ED.png)](https://blog.tensorflow.org/2023/06/on-device-fetal-ultrasound-assessment-with-tensorflow-lite.html?utm_source=email&utm_medium=newsletter&utm_campaign=tensorflow-june23) | | | | | | | | | | | |---| | |---| | |---| | |---| | [![](https://gstatic.com/growthlab/api/C2TRryY03aslRt6S7l4C2FVFxnGneHkpeq8VO4G7.png)](https://blog.tensorflow.org/2023/06/visualizing-and-interpreting-decision.html?utm_source=email&utm_medium=newsletter&utm_campaign=tensorflow-june23) | | Visualize and interpret decision trees with dtreeviz | | Use the dtreeviz library with **TensorFlow Decision Forests** to visualize how each decision node in a tree splits up a specific feature's domain and show the distribution of training instances in each prediction. | | |---| | |---| | |---| | |---|---| | |---| | [Read the blog](https://blog.tensorflow.org/2023/06/visualizing-and-interpreting-decision.html?utm_source=email&utm_medium=newsletter&utm_campaign=tensorflow-june23) | | |---| | [![](https://www.gstatic.com/growthlab/api/Obmfy5bg9fJotE3zdZDXu4HiZx1oT3KnprcfW3ED.png)](https://blog.tensorflow.org/2023/06/visualizing-and-interpreting-decision.html?utm_source=email&utm_medium=newsletter&utm_campaign=tensorflow-june23) | | | | | | | | | | | |---| | |---| | |---|---| | |---| | [Try it in Colab](https://colab.sandbox.google.com/github/tensorflow/decision-forests/blob/main/documentation/tutorials/dtreeviz_colab.ipynb?utm_source=email&utm_medium=newsletter&utm_campaign=tensorflow-june23) | | |---| | [![](https://www.gstatic.com/growthlab/api/Obmfy5bg9fJotE3zdZDXu4HiZx1oT3KnprcfW3ED.png)](https://colab.sandbox.google.com/github/tensorflow/decision-forests/blob/main/documentation/tutorials/dtreeviz_colab.ipynb?utm_source=email&utm_medium=newsletter&utm_campaign=tensorflow-june23) | | | | |---| | |---| | [![](https://gstatic.com/growthlab/api/8sQYrq1wzG8cGPHr4CYP2uQeQz78Mz1JQs9GL3N2.jpg)](https://blog.tensorflow.org/2023/06/augmenting-recommendation-systems-with.html?utm_source=email&utm_medium=newsletter&utm_campaign=tensorflow-june23) | | Augment recommendation systems with state-of-the-art LLMs | | Explore how you can use the [PaLM API](https://developers.generativeai.google/guide/palm_api_overview?utm_source=email&utm_medium=newsletter&utm_campaign=tensorflow-june23) to create recommendations in chat applications, generate and sort recommendations, use embeddings to retrieve unknown candidates, and more. | | |---| | |---| | |---| | |---|---| | |---| | [Read the blog](https://blog.tensorflow.org/2023/06/augmenting-recommendation-systems-with.html?utm_source=email&utm_medium=newsletter&utm_campaign=tensorflow-june23) | | |---| | [![](https://www.gstatic.com/growthlab/api/Obmfy5bg9fJotE3zdZDXu4HiZx1oT3KnprcfW3ED.png)](https://blog.tensorflow.org/2023/06/augmenting-recommendation-systems-with.html?utm_source=email&utm_medium=newsletter&utm_campaign=tensorflow-june23) | | | | | | | | | | | |---| | |---| | |---| | |---| | [![](https://gstatic.com/growthlab/api/f3U3S3h49PohJYfW0eXHfiLEs6JxXFR3D3cebCpT.jpg)](https://www.youtube.com/watch?v=7SdrrHpu8_o?utm_source%3Demail&utm_medium=newsletter&utm_campaign=tensorflow-june23) | | Transitioning from software engineering to ML engineering | | What are the key mindset differences between Machine Learning Engineering (MLE) and Software Engineering (SWE)? Find out what a typical workday looks like for each role, their complexities, and how they differ from planning to defining success. | | |---| | |---| | |---| | |---|---| | |---| | [Watch the video](https://notifications.google.com/g/proof/p/ADa0GC8UJL_0vFtYqcUfm3-rD9gbI9AIB4wiaYnHkXJ6FjXYYo73jS4nucmZbn0r5N3Seti_SQV7nI_WS7TYjjEaI24_l6po_u72jxALLGjUqhBEck2Pspq37YE6BQBxZoYcnG7fnHlzeRSxdSKoeZDIDvv4jnlDl4uIFTlir3vwnN8PBWSOSNpG7wYp5p2wobmeMKeA1tyvQZ10v_NspTBuXE5iTaNgWi9RxuB9UvIx0v6xSfC4Xs1_IVKRjzCKV4BtKtEyg7ZNdUlI1g9rNsy9k7elP6qeTt0) | | |---| | [![](https://www.gstatic.com/growthlab/api/Obmfy5bg9fJotE3zdZDXu4HiZx1oT3KnprcfW3ED.png)](https://www.youtube.com/watch?v=7SdrrHpu8_o?utm_source%3Demail&utm_medium=newsletter&utm_campaign=tensorflow-june23) | | | | | | | | | | | | | | |---| |   | | | |---| | ![](https://www.gstatic.com/gumdrop/files/spacer-11.gif) | | Stay Connected | | |---|---|---|---|---|---|---|---|---| | [![](https://www.gstatic.com/growthlab/api/e7WEFvQxwbiFjhuJkQsF5Fq09BSs8t0t7zjVc2ZZ.png)](https://blog.tensorflow.org) |   | [![](https://www.gstatic.com/growthlab/api/3oLbQMNQ8xdPTrZaFXgbpypikCrz1cifbZnJ7hYv.png)](https://github.com/tensorflow) |   | [![](https://www.gstatic.com/growthlab/api/WyYA2MSf4Sm1GSPGC3H8XppkwH31kkTlwMPlH0Nh.png)](https://twitter.com/tensorflow) |   | [![](https://www.gstatic.com/growthlab/api/Hmw6zspJ6zRcW9dalh8m4Yztyv80TMDVsycNLpCi.png)](https://www.youtube.com/tensorflow) |   | [![](https://www.gstatic.com/growthlab/api/o2mjGQiE1CeSDhViQ9I47utHTpyx929ckrYzUOoR.png)](https://discuss.tensorflow.org) | | | |---| | |---| | ![](https://www.gstatic.com/gumdrop/files/spacer-11.gif) | | |---| | © 2023 Google LLC 1600 Amphitheatre Parkway, Mountain View, CA 94043 | | | | | | | |

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