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. Learn more →
Tmu Alternatives
Similar projects and alternatives to tmu
-
nvitop
An interactive NVIDIA-GPU process viewer and beyond, the one-stop solution for GPU process management.
-
-
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.
-
-
catboost
A fast, scalable, high performance Gradient Boosting on Decision Trees library, used for ranking, classification, regression and other machine learning tasks for Python, R, Java, C++. Supports computation on CPU and GPU.
-
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.
-
NOTE:
The number of mentions on this list indicates mentions on common posts plus user suggested alternatives.
Hence, a higher number means a better tmu alternative or higher similarity.
tmu reviews and mentions
Posts with mentions or reviews of tmu.
We have used some of these posts to build our list of alternatives
and similar projects.
- Tsetlin machine – the other AI toolbooks
- Tsetlin Machine Unified (TMU) - One Codebase to Rule Them All
-
[R] New Tsetlin machine learning scheme creates up to 80x smaller logical rules, benefitting hardware efficiency and interpretability.
Code: https://github.com/cair/tmu
-
This Artificial Intelligence (AI) Research From Norway Introduces Tsetlin Machine-Based Autoencoder For Representing Words Using Logical Expressions
Quick Read: https://www.marktechpost.com/2023/01/10/this-artificial-intelligence-ai-research-from-norway-introduces-tsetlin-machine-based-autoencoder-for-representing-words-using-logical-expressions/ Paper: https://arxiv.org/pdf/2301.00709.pdf Github: https://github.com/cair/tmu
-
Do we really need 300 floats to represent the meaning of a word? Representing words with words - a logical approach to word embedding using a self-supervised Tsetlin Machine Autoencoder.
Here is a new self-supervised machine learning approach that captures word meaning with concise logical expressions. The logical expressions consist of contextual words like “black,” “cup,” and “hot” to define other words like “coffee,” thus being human-understandable. I raise the question in the heading because our logical embedding performs competitively on several intrinsic and extrinsic benchmarks, matching pre-trained GLoVe embeddings on six downstream classification tasks. Thanks to my clever PhD student Bimal, we now have even more fun and exciting research ahead of us. Our long term research goal is, of course, to provide an energy efficient and transparent alternative to deep learning. You find the paper here: https://arxiv.org/abs/2301.00709 , an implementation of the Tsetlin Machine Autoencoder here: https://github.com/cair/tmu, and a simple word embedding demo here: https://github.com/cair/tmu/blob/main/examples/IMDbAutoEncoderDemo.py.
-
A note from our sponsor - InfluxDB
www.influxdata.com | 25 Apr 2024
Stats
Basic tmu repo stats
5
108
9.2
about 1 month ago
cair/tmu is an open source project licensed under MIT License which is an OSI approved license.
The primary programming language of tmu is Python.
Sponsored
SaaSHub - Software Alternatives and Reviews
SaaSHub helps you find the best software and product alternatives
www.saashub.com