instadeep.com的 10 大竞争对手

deeppcb.ai

Design complex boards effortlessly, no expertise needed with DeepPCB, the pure AI-powered, cloud-native PCB routing software by InstaDeep.

ai.io

3DAT is an AI platform for markerless motion capture, extracting biomechanical data from video to analyze movement with pro-grade accuracy

impel.ai

For this week’s Motor Trade Radio episode, Impel’s Chief Product Officer Matt Muilenburg joins the hosts to dig into how AI is redefining automotive retail on both sides of the Atlantic. Matt shares Impel’s decade-long evolution in Automotive AI, the company’s rapid growth in the...

sewerai.com

AI-powered sewer inspection analysis and management. 6× faster reviews with 99% defect detection accuracy. Built for utilities, engineers, and contractors.

duality.ai

Can advanced internet AI models be harnessed to make robots smarter and safer — making them our natural collaborators? We explore Embodied AI, and how digital twin simulation can be its bridge.

odsc.com

ODSC is the top applied data science training conference! Attend one of our AI events to learn more about how you can build AI today.

biontech.com

BioNTech guides you through the promising world of immunotherapies. Find information on basic research and new developments of new treatment options.

trendtracker.ai

Trendtracker scouts, monitors and forecasts emerging trends, signals in any industry and geography. It discovers top startups, provides personalised news with automated summaries, and more other data-driven, in-depth insights to gain a competitive edge in a fast-changing business landscape.

lightgbm.readthedocs.io

Tree based algorithms can be improved by introducing boosting frameworks. LightGBM is one such framework, based on Ke, Guolin et al. (2017) . This package offers an R interface to work with it. It is designed to be distributed and efficient with the following advantages: 1. Faster training speed and higher efficiency. 2. Lower memory usage. 3. Better accuracy. 4. Parallel learning supported. 5. Capable of handling large-scale data. In recognition of these advantages, LightGBM has been widely-used in many winning solutions of machine learning competitions. Comparison experiments on public datasets suggest that LightGBM can outperform existing boosting frameworks on both efficiency and accuracy, with significantly lower memory consumption. In addition, parallel experiments suggest that in certain circumstances, LightGBM can achieve a linear speed-up in training time by using multiple machines.

papers.cool

explore the latest in academic research with cool papers. our platform, powered by kimi chat ai, streamlines the discovery of arxiv and top conference papers, offering an interactive faq for quick insights.