MLKit: A Simple Machine Learning Framework Written in Swift

MLKit (a.k.a Machine Learning Kit) 🤖

MLKit is a simple machine learning framework written in Swift. Currently MLKit features machine learning algorithms that deal with the topic of regression, but the framework will expand over time with topics such as classification, clustering, recommender systems, and deep learning. The vision and goal of this framework is to provide developers with a toolkit to create products that can learn from data. MLKit is a side project of mine in order to make it easier for developers to implement machine learning algorithms on the go, and to familiarlize myself with machine learning concepts.

This project is under active development and is not ready for use in commercial or personal projects.   

MachineLearningKit Reference

Requirements

Installation

Cocoapods

Add pod 'MachineLearningKit to your PodFile and then run pod install.

Without Cocoapods

  1. Download the repository.
  2. cd [Project_Path_Goes_Here]/Example
  3. pod install

Contributing

The mission of this project is to give developers the ability to incorporate Machine Learning algorithms into their projects with ease and to enable the creation of advanced projects using the Swift programing language. With this being said, I encourage all developers interested in making Machine Learning accessible to the anyone who works with iOS apps and TVOS apps to contribute to this project.

To contribute an algorithm not currently available within the framework, please create an issue and state what algorithm you have implemented. Make sure that there are unit tests involved where applicable. Also, provide a brief overview of how to use your algorithm. You are also welcome to impelment algorithms within the Roadmap section (below).

To contribute to an already existant algorithm within the framework, please create an issue and state any changes or additions you have made.


Wiki

Example Project

⚠️️ The Flappy Bird Example Project is located in the Example folder. When you run the example you will see the fitness and the decisions that each Flappy Bird is making. The example project has comments to help with understanding how it was made.


Roadmap:

  •  KMeans++ Implementation
  •  KMeans Clustering Documentation
  •  Neural Network Documentation
  •  Logistic Regression
  •  Decision Trees

Future Releases:

  •  Convolutional Neural Network
  •  Recurrent Neural Network
  •  Artificial Neural Network using Metal
  •  Game Playing AI (MiniMax, Alpha-Beta Pruning)
  •  Self Organizing Maps

Features (So Far)

  •  Matrix and Vector Operations (uses Upsurge framework)
  •  Simple Linear Regression (Allows for 1 feature set)
  •  Polynomial Regression (Allows for multiple features)
  •  Ridge Regression
  •  Multi-Layer Feed Forward Neural Network
  •  K-Means Clustering
  •  Genetic Algorithms
  •  Allows for splitting your data into training, validation, and test sets.
  •  K-Fold Cross Validation & Ability to test various L2 penalties for Ridge Regression
  •  Single Layer Perceptron, Multi-Layer Perceptron, & Adaline ANN Architectures

Frameworks that MLKit uses

  • 🙌 Upsurge (Matrix and Vector Operations)
  • 🙌 CSVReader (CSV Reading) (Used in Unit Testing)

Development Schedule

Week of August 28th

TBD

License

MIT License

Copyright (c) 2017 Guled Ahmed

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.


Author: Somnibyte
Source code: https://github.com/Somnibyte/MLKit
License: MIT license

#swift #machine-learning 

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  • Investment predictions
  • Customer service
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  • Marketing
  • Network security
  • Loan underwriting
  • Algorithmic trading
  • Process automation
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  • Content creation
  • Trade settlements
  • Money-laundering prevention
  • Custom machine learning solutions

Education industry

Education industry is one of the industries which is investing in machine learning as it offers more efficient and easierlearning.AdaptiveLearning,IncreasingEfficiency,Learning Analytics,Predictive Analytics,Personalized Learning,Evaluating Assessments etc are the applications of machine learning in the education industry.

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  • Rise of Robots

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Today most of the business from different industries are hire machine learning developers in India and achieve their business goals. This technology may have multiple applications, and, interestingly, it hasn’t even started yet but having taken such a massive leap, it also opens up so many possibilities in the existing business models in such a short period of time. There is no question that the increase of machine learning also brings the demand for mobile apps, so most companies and agencies employ Android developers and hire iOS developers to incorporate machine learning features into them.

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Transportation industry

Machine learning is one of the technologies that have already begun their promising marks in the transportation industry.Autonomous Vehicles,Smartphone Apps,Traffic Management Solutions,Law Enforcement,Passenger Transportation etc are the applications of AI and ML in the transportation industry.Following challenges in the transportation industry can be solved by machine learning and Artificial Intelligence.

  • ML and AI can offer high security in the transportation industry.
  • It offers high reliability of their services or vehicles.
  • The adoption of this technology in the transportation industry can increase the efficiency of the service.
  • In the transportation industry ML helps scientists and engineers come up with far more environmentally sustainable methods for powering and operating vehicles and machinery for travel and transport.

Healthcare industry

Technology-enabled smart healthcare is the latest trend in the healthcare industry. Different areas of healthcare, such as patient care, medical records, billing, alternative models of staffing, IP capitalization, smart healthcare, and administrative and supply cost reduction. Hire dedicated machine learning developers for any of the following applications.

  • Identifying Diseases and Diagnosis
  • Drug Discovery and Manufacturing
  • Medical Imaging Diagnosis
  • Personalized Medicine
  • Machine Learning-based Behavioral Modification
  • Smart Health Records
  • Clinical Trial and Research
  • Better Radiotherapy
  • Crowdsourced Data Collection
  • Outbreak Prediction

**
Finance industry**

In financial industries organizations like banks, fintech, regulators and insurance are Adopting machine learning to improve their facilities.Following are the use cases of machine learning in finance.

  • Fraud prevention
  • Risk management
  • Investment predictions
  • Customer service
  • Digital assistants
  • Marketing
  • Network security
  • Loan underwriting
  • Algorithmic trading
  • Process automation
  • Document interpretation
  • Content creation
  • Trade settlements
  • Money-laundering prevention
  • Custom machine learning solutions

Education industry

Education industry is one of the industries which is investing in machine learning as it offers more efficient and easierlearning.AdaptiveLearning,IncreasingEfficiency,Learning Analytics,Predictive Analytics,Personalized Learning,Evaluating Assessments etc are the applications of machine learning in the education industry.

Outsource your machine learning solution to India,India is the best outsourcing destination offering best in class high performing tasks at an affordable price.Business** hire dedicated machine learning developers in India for making your machine learning app idea into reality.
**
Future of machine learning

Continuous technological advances are bound to hit the field of machine learning, which will shape the future of machine learning as an intensively evolving language.

  • Improved Unsupervised Algorithms
  • Increased Adoption of Quantum Computing
  • Enhanced Personalization
  • Improved Cognitive Services
  • Rise of Robots

**Conclusion
**
Today most of the business from different industries are hire machine learning developers in India and achieve their business goals. This technology may have multiple applications, and, interestingly, it hasn’t even started yet but having taken such a massive leap, it also opens up so many possibilities in the existing business models in such a short period of time. There is no question that the increase of machine learning also brings the demand for mobile apps, so most companies and agencies employ Android developers and hire iOS developers to incorporate machine learning features into them.

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