Machine Learning is a type of Artificial Intelligence that allows software applications to learn from the data and become more precise in predicting outcomes without human intervention.
A machine learning framework is an interface that allows developers to build and deploy machine learning models faster and easier.
There are three types of Machine Learning like,
- Supervised Learning
- Unsupervised Learning
- Reinforcement Learning
When considering whether to build or buy a machine learning framework, it is important to:
- Understand the costs and benefits of both options.
- Figure out the technical resources you would need to maintain an ongoing machine learning lifecycle in both conditions.
- Be a champion of the transformational capabilities of enterprise machine learning at your organization.
Top 10 Machine Learning Frameworks:
- Sonnet: Sonnet is best utilized for creating complicated neural network structures in TensorFlow. Easy to use – integrate and possesses efficient libraries to support.
- Keras: It is considered a preferred choice for beginners; Python based developers and assists in coding precisely and effectively. There is an inbuilt support for data parallelism.
- Caffe: Caffe signifies “Convolutional Architecture for Fast Feature Embedding”. It is a popular deep learning framework that is written in C++.
- Apache Mahout: Apache Mahout has its main focus on linear algebra and statistical engines.
- Apache Spark: Apache Spark is an open source ML framework that offers programming interface for complete clusters.
- Accord .Net: Accord .NET is a popular ML framework that offers complete focus on areas like neural networks, regression, statistics, clustering etc. It also handles audio / video processing libraries. These libraries exist as the base code as well as different packages.
- Gluon: Gluon has been a current add-on to the popular ML frameworks. It allows the users to choose from a dynamic neural network and any structure they wish to select from.
- Firebase ML Kit: Google came up with a novel idea of Firebase ML Kit – a strong contender in the list of ML frameworks. Firebase ML Kit gives image labelling, text recognition and object categorization.
- Apple’s Core ML: it was made for iOS, TVOS apps and macOS. Apple’s Core ML is a user-friendly framework, easily adaptable by novices.
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