Skip to main content

Private library using Web3

Project description

wiseAI

wiseAI: Simplify Your Machine Learning Workflow

Introduction: Welcome to wiseAI, the ultimate machine learning library designed specifically! Whether you are a seasoned data scientist or a business analyst venturing into the world of machine learning, wiseAI offers an intuitive and powerful platform to streamline your model development process.

Key Features:

  • User-Friendly Interface: wiseAI provides a simple, yet powerful interface that allows users to build and deploy machine learning models with minimal coding.
  • Comprehensive Preprocessing Tools: From data cleaning to feature engineering, our library includes a wide array of preprocessing tools to prepare your data efficiently.
  • Model Selection and Evaluation: Easily compare multiple algorithms and choose the best-performing model with our built-in evaluation metrics and visualizations.
  • Automation and Hyperparameter Tuning: Automate repetitive tasks and optimize model performance with advanced hyperparameter tuning techniques.
  • Scalability: Designed to handle large datasets and integrate seamlessly with big data platforms, ensuring models are ready for enterprise-level deployment.
  • Support: Dedicated support developer to assist you in every step of your machine learning journey.

Why Choose wiseAI?

  1. Efficiency: Save time and resources with automated workflows and optimized processes.
  2. Accessibility: Make machine learning accessible to a broader audience within your organization.
  3. Flexibility: Adaptable to various business needs and industry-specific applications.
  4. Integration: Compatible with popular data science tools and frameworks, allowing for smooth integration into existing workflows.

Getting Started:

  1. Install wiseAI using pip:
    pip install wiseAI
    
  2. Training Model
    test_model = AutoBinaryML(
        model_name= 'test_model'
        , model_version = 'v1'
        , train_data = data
        , label = 'target'
        , time_limit = 60*5 
    )
    test_model.fit()
    
  3. Predict
    predicts = test_model.batch_prediction(data, 'predict')
    

Transform data into actionable insights with wiseAI. Start your machine learning journey today and see the difference!


Elevate machine learning capabilities with wiseAI, where simplicity meets power.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

wiseai-1.0.0b20240610.tar.gz (10.8 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

wiseAI-1.0.0b20240610-py3-none-any.whl (16.8 kB view details)

Uploaded Python 3

File details

Details for the file wiseai-1.0.0b20240610.tar.gz.

File metadata

  • Download URL: wiseai-1.0.0b20240610.tar.gz
  • Upload date:
  • Size: 10.8 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.1.0 CPython/3.9.19

File hashes

Hashes for wiseai-1.0.0b20240610.tar.gz
Algorithm Hash digest
SHA256 f5bd71416fe3b071c2da4189c6daa986c6fa6e0f0d8af6cf9a21ffe3adbffc3c
MD5 9dd4c783ae268a15785769c01a15c1de
BLAKE2b-256 ff4792a612348e0ec4a1631679f038c26121975639f4bd17e70db5051fd5f27e

See more details on using hashes here.

File details

Details for the file wiseAI-1.0.0b20240610-py3-none-any.whl.

File metadata

File hashes

Hashes for wiseAI-1.0.0b20240610-py3-none-any.whl
Algorithm Hash digest
SHA256 6d7cb58c664de1c002df9809b1887b97f09bf46157e2c1da898363f6194f4990
MD5 ddcdff24fb6fa1f0b9da6f82d7b0ff4c
BLAKE2b-256 41c84f9edc46b6aa738c64060efdec1ccb0bd01f075a67f7be526598ac7dce1c

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page