SaaSHub helps you find the best software and product alternatives Learn more →
Gonb Alternatives
Similar projects and alternatives to gonb
-
InfluxDB
Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.
-
Arraymancer
A fast, ergonomic and portable tensor library in Nim with a deep learning focus for CPU, GPU and embedded devices via OpenMP, Cuda and OpenCL backends
-
WorkOS
The modern identity platform for B2B SaaS. The APIs are flexible and easy-to-use, supporting authentication, user identity, and complex enterprise features like SSO and SCIM provisioning.
-
ipe
Discontinued An open source Pusher server implementation compatible with Pusher client libraries written in GO
-
nimCSO
nim Composition Space Optimization is a high-performance tool leveraging metaprogramming to implement several methods for selecting components (data dimensions) in compositional datasets, as to optimize the data availability and density for applications such as machine learning.
-
Juju
Orchestration engine that enables the deployment, integration and lifecycle management of applications at any scale, on any infrastructure (Kubernetes or otherwise).
-
SaaSHub
SaaSHub - Software Alternatives and Reviews. SaaSHub helps you find the best software and product alternatives
gonb reviews and mentions
-
Go, Python, Rust, and production AI applications
I've had these strong feelings and the OP describes it really well. Despite being a polyglot programmer, I really struggle with Python, both in expression and performance (unless it's just config for GPUs).
Some of this frustration was recently an "Unpopular Opinion" on the Go Time Podcast regarding Python being great for "data exploration" but not for "data engineering": https://changelog.com/gotime/304#t=3196
I've been yearning for better interactive tooling and ML-related libraries bridge this gap and started using some even in just the last week:
* GoNB (Golang-support for Jupyter notebooks, also from a Googler) https://github.com/janpfeifer/gonb
* That uses Go-Plotly for graphs/UI: https://github.com/MetalBlueberry/go-plotly
* GoMLX (GoNB author is also on that project, many thanks Jan!) https://github.com/gomlx/gomlx
* Hidden at the end of OP is LangChainGo for LLMs, which I haven't used yet: https://github.com/tmc/langchaingo
Pick those up and let's make the Go community stronger together!
-
The Golang Saga: A Coder’s Journey There and Back Again. Part 2: The Data Expedition
When I created a new Jupyter file in Go, I faced a challenge trying to replicate the development process I usually follow with Python. In Python and Jupyter Notebook I can conveniently run code in separate parts, saving previous values in memory and using cells to organize code. This flexibility was missing in Go, and it took me some time to figure out a solution. However, I came across a helpful tutorial that explained how to use caching with the Go Kernel, making the process smoother with gonb.
-
The Golang Saga: A Coder’s Journey There and Back Again. Part 1: Leaving the Shire
I needed one more thing to make myself feel at home, something I usually use with Python. When working with data, I often turned to the Jupyter VSCode extension for its convenience. To my relief, I discovered that a Go kernel existed, tailored perfectly for my needs.
-
GoMLX -- Accelerated ML for Go
Training library, with some pretty-printing. Including plots for GoNB Jupyter notebook.
-
GoNB, a new Jupyter Notebook Kernel for Go
Tutorial (and demo) here. Source code in github.com/janpfeifer/gonb.
-
A note from our sponsor - SaaSHub
www.saashub.com | 26 Apr 2024
Stats
janpfeifer/gonb is an open source project licensed under MIT License which is an OSI approved license.
The primary programming language of gonb is Go.
Sponsored