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|GNU General Public License v3.0 only||Apache License 2.0|
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
- Machine Learning that is built-in SQL and databases
- Machine Learning via SQL
- Awesome GitHub project - MindsDB: In-Database Machine Learning
GitHub/MindsDB: In-Database Machine Learning
1 project | reddit.com/r/coolgithubprojects | 26 May 2022
Show HN: PostgresML, now with analytics and project management
4 projects | news.ycombinator.com | 2 May 2022
In-Database Machine Learning
1 project | news.ycombinator.com | 29 Apr 2022
MindsDB ML-SQL Server enables machine learning workflows using SQL
1 project | news.ycombinator.com | 24 Apr 2022
[D] AutoML vs AI Tables. Is it a new rival for Self-Service Machine Learning?
1 project | reddit.com/r/MachineLearning | 9 Mar 2022
I represent a community-driven open source project called MindsDB (see on GitHub). We need your feedback about our concept for doing machine learning using SQL! It is called AI Tables and aims to democratize machine learning for all who work with data. There's an article on Medium with SQL commands examples.
Self-Service Machine Learning with Intelligent Databases
1 project | dev.to | 9 Mar 2022
AI Tables is a part of GitHub project by MindsDB and are available as open-source or as a managed cloud service. They integrate with traditional SQL and NoSQL databases and data streams like Kafka & Redis.
MindsDB: Creating machine learning predictive models using SQL.
2 projects | dev.to | 19 Jan 2022
Want to try it out for yourself? Sign up for a free MindsDB account and join our community! Engage with MindsDB community on Slack or Github to ask questions, share and express ideas and thoughts!
Level up your Python today with open-source contributions
11 projects | dev.to | 25 May 2022
Read the contributing guidelines
Should you shuffle the input for a word2vec negative sampling model before or after assigning negative context pairs for each target word?
1 project | reddit.com/r/MLQuestions | 17 May 2022
I may have a few trust issues with the shuffle argument of keras' model.fit(), after experiencing this bug regarding shuffle='batch' first hand.
2 projects | reddit.com/r/u_Animus_Vacui | 9 May 2022
Has anyone ever experienced this ? details in the comments.
1 project | reddit.com/r/learnmachinelearning | 7 May 2022
it seems like other people have had this issue like another user mentioned when using dropout or BN (https://github.com/keras-team/keras/issues/6977) , the model does use dropout so that maybe it .
How to define max_queue_size, workers and use_multiprocessing in keras fit_generator()?
1 project | reddit.com/r/codehunter | 5 May 2022
Detailed explanation of model.fit_generator() parameters: queue size, workers and use_multiprocessing
Negative dimension size caused by subtracting 3 from 1 for 'Conv2D'
2 projects | reddit.com/r/codehunter | 27 Apr 2022
I'm using Keras with Tensorflow as backend , here is my code:
1 project | reddit.com/r/learnprogramming | 25 Apr 2022
How to get reproducible results in keras
2 projects | reddit.com/r/codehunter | 13 Apr 2022
Install Keras (http://keras.io/)
20+ Free Tools & Resources for Machine Learning
5 projects | dev.to | 31 Mar 2022
Keras Keras is an API for neural networks that helps doing quick research.
Installing Python3 in Linux
9 projects | dev.to | 28 Mar 2022
According to IBM, Artificial Intelligence (AI) is technology that instructs computers to mimic the human mind in decision-making and problem-solving. Machine Learning (ML) is a subset of AI that consist of procedures that leverage on mathematical data models and algorithms to make predictions. Python implements ML and AI with generally fewer lines of code and pre-built libraries and being a scientific language also comes in support of these technologies. Some of the libraries used in AI and ML include: Tensorflow, Scikit-Learn, Numpy, Keras, Theano
What are some alternatives?
MLP Classifier - A handwritten multilayer perceptron classifer using numpy.
scikit-learn - scikit-learn: machine learning in Python
tensorflow - An Open Source Machine Learning Framework for Everyone
xgboost - Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C++ and more. Runs on single machine, Hadoop, Spark, Dask, Flink and DataFlow
TFLearn - Deep learning library featuring a higher-level API for TensorFlow.
Prophet - Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth.
pytorch-lightning - The lightweight PyTorch wrapper for high-performance AI research. Scale your models, not the boilerplate.
Pandas - Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more
skflow - Simplified interface for TensorFlow (mimicking Scikit Learn) for Deep Learning
Pytorch - Tensors and Dynamic neural networks in Python with strong GPU acceleration