Search Results for "self learning"

Halfrost-Field is a large public “knowledge and blog repository” maintained by a developer who documents a wide variety of computer-science, programming, and machine-learning content — from classic algorithms, ML fundamentals, to system design and broader engineering topics. The repository is structured like a personal technical blog/book: it contains “contents” directories with Markdown-based notes, tutorials and guides. For example, there is a full machine learning course outline (regression, neural networks, SVMs, unsupervised learning, anomaly detection, large-scale ML, even application examples like OCR), that reads like a self-study curriculum. ...

...The platform observes agent tasks and user feedback in real time, offering robust observability into workflows and helping teams understand how agents perform over time. Acontext also supports agent self-learning by distilling structured skills and experiences from previously completed tasks, which can later be reused or searched to improve future performance. It includes tools to interact with session data, background agents that monitor progress, and a dashboard that visualizes success rates, artifacts, and learned skills. By combining persistent storage, observability, and learning capabilities, Acontext aims to make AI agents more scalable, reliable, and capable.

Go 101 is a series of books on Go programming. Currently, the following books are available. Go (Fundamentals) 101, which focuses on Go syntax/semantics (except custom generics related) and all kinds of runtime related things. Go Generics 101, which explains Go custom generics in detail. Go Optimizations 101, which provides some code performance optimization tricks, tips, and suggestions. Go Details & Tips 101, which collects many details and provides several tips in Go programming. These...

Go Katas is a curated collection of practice exercises and coding challenges specifically crafted to improve proficiency in Go, including idiomatic patterns, language fundamentals, and algorithm design. It mirrors the kata practice tradition from martial arts—repetitive, thoughtful practice where each exercise reinforces technique, discipline, and problem-solving approach. Each kata prompt focuses on a precise aspect of Go, such as concurrency patterns, memory management, interfaces, error...

A Machine Learning library written in pure Go designed to support relevant neural architectures in Natural Language Processing. Spago is self-contained, in that it uses its own lightweight computational graph both for training and inference, easy to understand from start to finish. The core module of Spago relies only on testify for unit testing.

As Go has received more and more attention, there have been more and more related articles, software, and resources. Go Language Lovers Weekly aims to share with you a week of Go language-related content that is worth knowing and learning. Published every Sunday. Contributions, recommended or self-recommended articles/software/resources are welcome, please submit an issue. Welcome to pay attention to our public account and get the weekly magazine as soon as possible. Weekly magazine for Go language lovers, published every Sunday.

Open Application Model (OAM) is a set of standard yet higher-level abstractions for modeling cloud-native applications on top of today's hybrid and multi-cloud environments. Focused on application rather than container or orchestrator, Open Application Model brings modular, extensible, and portable design for defining application deployment with higher level API. This is the key to enabling simple, consistent yet robust application delivery across hybrid environments including Kubernetes,...

Heartbleed contains a compact, purpose-built implementation for detecting the infamous Heartbleed vulnerability in OpenSSL’s TLS heartbeat extension (CVE-2014-0160). It focuses on demonstrating and testing the flaw rather than being a general-purpose security toolkit, which makes the code approachable for learning and auditing. The project illustrates how a malformed heartbeat request could coax vulnerable servers into leaking memory contents, including potentially sensitive data. Because it’s small and self-contained, it’s often used as a reference to understand the vulnerability mechanics without wading through large codebases. The repo also serves as a historical snapshot of a watershed moment in modern Internet security and the practical lessons it forced the industry to learn. ...