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features
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support

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Write a Review

Description

You can develop on your laptop, then scale the same Python code elastically across hundreds or GPUs on any cloud. Ray converts existing Python concepts into the distributed setting, so any serial application can be easily parallelized with little code changes. With a strong ecosystem distributed libraries, scale compute-heavy machine learning workloads such as model serving, deep learning, and hyperparameter tuning. Scale existing workloads (e.g. Pytorch on Ray is easy to scale by using integrations. Ray Tune and Ray Serve native Ray libraries make it easier to scale the most complex machine learning workloads like hyperparameter tuning, deep learning models training, reinforcement learning, and training deep learning models. In just 10 lines of code, you can get started with distributed hyperparameter tune. Creating distributed apps is hard. Ray is an expert in distributed execution.

Description

Weka comprises a suite of machine learning algorithms designed for various data mining activities. This platform offers functionalities for tasks such as data preparation, classification, regression, clustering, association rule mining, and data visualization. Interestingly, Weka is also the name of a flightless bird native to New Zealand, known for its curious disposition. The pronunciation of the name and the sounds made by the bird can be found online. As an open-source software, Weka is available under the GNU General Public License. We have created several complimentary online courses aimed at teaching machine learning and data mining through Weka, with video resources accessible on YouTube. The emergence and implementation of machine learning techniques represent a groundbreaking advancement in the realm of computer science. These techniques empower computer programs to systematically analyze extensive datasets and discern the most pertinent information. Consequently, this distilled knowledge can facilitate automated predictions and accelerate decision-making processes for individuals and organizations alike. This intersection of nature and technology showcases the fascinating ways in which we draw inspiration from the world around us.

API Access

Has API Yes 

API Access

Has API No 

Screenshots View All

Screenshots View All

Integrations

AWS Marketplace No 
Amazon EC2 Trn2 Instances Yes 
Amazon EKS Yes 
Amazon SageMaker Yes 
Amazon Web Services (AWS) Yes 
Apache Airflow Yes 
Azure Kubernetes Service (AKS) Yes 
Dask Yes 
Databricks Yes 
Feast Yes 
Flyte Yes 
Google Cloud Platform Yes 
Google Kubernetes Engine (GKE) Yes 
LanceDB Yes 
MLflow Yes 
Python Yes 
Snowflake Yes 
TensorFlow Yes 
Union Cloud Yes 
io.net Yes 

Integrations

AWS Marketplace Yes 
Amazon EC2 Trn2 Instances No 
Amazon EKS No 
Amazon SageMaker No 
Amazon Web Services (AWS) No 
Apache Airflow No 
Azure Kubernetes Service (AKS) No 
Dask No 
Databricks No 
Feast No 
Flyte No 
Google Cloud Platform No 
Google Kubernetes Engine (GKE) No 
LanceDB No 
MLflow No 
Python No 
Snowflake No 
TensorFlow No 
Union Cloud No 
io.net No 

Pricing Details

Free
Open source. Consumption-based.
Free Trial Yes 
Free Version Yes 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Deployment

Web-Based Yes 
On-Premises Yes 
iPhone App No 
iPad App No 
Android App No 
Windows Yes 
Mac Yes 
Linux Yes 
Chromebook No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Types of Training

Training Docs Yes 
Webinars Yes 
Live Training (Online) Yes 
In Person Yes 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

Vendor Details

Company Name

Anyscale

Founded

2019

Country

United States

Website

ray.io

Vendor Details

Company Name

University of Waikato

Country

New Zealand

Website

www.cs.waikato.ac.nz/ml/weka/

Product Features

Deep Learning

Convolutional Neural Networks No 
Document Classification No 
Image Segmentation No 
ML Algorithm Library No 
Model Training No 
Neural Network Modeling No 
Self-Learning No 
Visualization No 

Machine Learning

Deep Learning No 
ML Algorithm Library No 
Model Training No 
Natural Language Processing (NLP) No 
Predictive Modeling No 
Statistical / Mathematical Tools No 
Templates No 
Visualization No 

Product Features

Machine Learning

Deep Learning No 
ML Algorithm Library Yes 
Model Training No 
Natural Language Processing (NLP) No 
Predictive Modeling Yes 
Statistical / Mathematical Tools No 
Templates No 
Visualization Yes 

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