Keras
TensorFlow
PyTorch
Scikit-learn
TFlearn
OpenCV
Clarifai
Microsoft Cognitive Toolkit (Formerly CNTK)
Lichess
Chess.com
Lucas Chess
Chess Tempo Database
Chessmaster
Fritz
XBoard
DecodeChess
LichessBased on our record, Lichess seems to be a lot more popular than Keras. While we know about 894 links to Lichess, we've tracked only 31 mentions of Keras. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
As a beginner, I was looking for something simple and flexible for developing deep learning models and that is when I found Keras. Many AI/ML professionals appreciate Keras for its simplicity and efficiency in prototyping and developing deep learning models, making it a preferred choice, especially for beginners and for projects requiring rapid development. - Source: dev.to / 30 days ago
After setting the variables for the environment, the next step is to install dependencies. To use Gemma, KerasNLP is the dependency used. KerasNLP is a collection of natural language processing (NLP) models implemented in Keras and runnable on JAX, PyTorch, and TensorFlow. - Source: dev.to / about 1 month ago
Other popular machine learning tools include PyTorch, Keras, and Scikit-learn. PyTorch is an open-source machine learning library developed by Facebook that is known for its ease of use and flexibility. Keras is a high-level neural networks API that is written in Python and is known for its simplicity. Scikit-learn is a machine learning library for Python that is used for data analysis and data mining tasks. - Source: dev.to / 11 months ago
I'm not aware of anything off-the-shelf, but if you have sufficient programming experience, one way to do this would be to build a large dataset of reference images and pictures and use something like keras to train a convolutional neural network on them. Source: about 1 year ago
Pandas comes with many complex tabular data operations. And, since it exists in a Python environment, it can be coupled with lots of other powerful libraries, such as Requests (for connecting to other APIs), Matplotlib (for plotting data), Keras (for training machine learning models), and many more. - Source: dev.to / over 1 year ago
Once you’re finished, we’re going to set up a lichess bot account. Head over to https://lichess.org/ and create a new account. - Source: dev.to / 25 days ago
Https://lichess.org/ The best I’ve found. It’s also crowd funded and they talk about their interest tech as well. - Source: Hacker News / 4 months ago
If you want to improve make it your goal to play the best chess you can, not increase an arbitrary number. Watch YouTube series like John Bartholomew's "Climb the Rating Ladder" for some general insight into what you might be doing wrong. Read Irving Chernev's "Logical Chess: Move By Move" to see the thinking process of high level players. Do lots of puzzles (I like lichess.org for puzzles). And always analyze... Source: 5 months ago
The easiest way to play against Stockfish is perhaps on https://lichess.org/, but it's not the only chess engine that evaluates positions with a neural network. Source: 6 months ago
If you actually like chess, try lichess.org, the free and open-source, no ads ever, premium alternative. Source: 6 months ago
TensorFlow - TensorFlow is an open-source machine learning framework designed and published by Google. It tracks data flow graphs over time. Nodes in the data flow graphs represent machine learning algorithms. Read more about TensorFlow.
Chess.com - Play chess on Chess.
PyTorch - Open source deep learning platform that provides a seamless path from research prototyping to...
Lucas Chess - The aim is to play chess against the computer with increasing levels of difficulty and with a...
Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.
Chess Tempo Database - Chess Tempo Database gives you a library of more than 2 million searchable chess games.