#jupyter_notebook#jax
Flax is a library for creating neural networks with JAX. It offers a flexible way to build and analyze these networks. The new Flax NNX API makes it easier to work with neural networks by using regular Python objects, which helps in creating, debugging, and analyzing models more efficiently. This means users can express their models in a more intuitive way, making it simpler to develop and modify neural networks. Flax also provides many tools and examples to help users get started quickly.
https://github.com/google/flax
#java
The Model Context Protocol (MCP) Java SDK helps developers connect AI models with tools and data sources using a standardized interface. It supports both synchronous and asynchronous communication, making it flexible for different applications. The SDK includes features like tool management, logging, and multiple transport options, which simplify interactions between AI systems and external tools. This benefits users by providing a consistent way to integrate AI with various data sources, reducing the complexity of managing multiple connectors for different tools.
https://github.com/modelcontextprotocol/java-sdk
#java
BookLore is a self-hosted web app that helps you organize, manage, and read your personal book collection easily. You can sort books into libraries and shelves, automatically get book details from sources like Goodreads, and track your reading progress on PDFs and eBooks with a built-in reader. It supports multiple users with separate accounts and secure login options, so everyone can manage their own books without mixing collections. You can upload many books at once, share books by email (great for Kindle users), and browse books via compatible reading apps. This gives you full control over your digital library with a clean, modern interface and continuous updates[1][2][5].
https://github.com/adityachandelgit/BookLore
JSpecify — стандартизация Java-аннотаций для статического анализа кода и взаимодействия между языками JVM.
Если вы знакомы с Java или изучали исходный код, то одним из решений проблемы null является использование аннотаций nullability. Однако реализаций таких аннотаций много: JetBrains, Android Jetpack, Spring, Uber и другие создали свои версии.
Решений очень много, и возникла проблема выбора и поддержки. Хотелось бы иметь стандарт в Java, но договориться не удалось.
Консорциум компаний и команд из Google, JetBrains, Meta, Kotlin, Android, Spring, PMD, Sonar, EISOP и других объединился и создал единый стандарт, который обязуются поддерживать в своих решениях.
JSpecify 1.0 сосредоточен на nullability и содержит четыре аннотации: @NonNull, @Nullable, @NullMarked, @NullUnmarked.
Интеграция уже началась в библиотеки Jetpack Android и Kotlin.
#java
Java Backend
1 - dars. Kirish
- JVM, JRE, JDK
- Java qanday ishlaydi?
- O‘zgaruvchilar
- Maʼlumot turlari
- Kommentariyalar
- Chiqarish
Mentor : Hasan Po‘latov
#java
👉@ummat_uchun_dasturlash