In the age of rapid digitisation, the IT market has software that can enable businesses to apply machine learning algorithms conveniently. This way, experts can benefit from rapid prototyping and more functionality with the help of additional tools. The industry has numerous services available for designing machine learning software. The following article discusses the top 10 ML technologies in the sector.
Famous 10 Machine Learning Software to Modernise Business Operations
ML models are a subdivision of AI software. It allows businesses to process large volumes of data without lowering the quality of results. The sections below will highlight the most popular software solutions that can support specialists in building machine learning models.
The official name for ML-based solutions in the Data Science sector is TensorFlow. It is a free software platform for ML procedures. This way, experts can streamline business operations. Moreover, the cutting-edge solution supports dataflow & differentiable programming. TensorFlow supports the building of statistical ML solutions and Deep Learning (DL) with the help of CUDA GPUs.
The basic type of TensorFlow is a multidimensional array which is a free toolkit that facilitates efficient data processing. It also supports ML-based applications like computer vision, NLP, & reinforcement learning.
Shogun is a famous free machine learning software that is written in C++ language, which supports Python, Ruby & C# programming. Following are some algorithms that Shogun supports:
- Support VEctor MAchines
- Dimensionality Reduction
- Clustering Algorithms
- Hidden Markov Models
- Linear Discriminant Analysis
Apache Mahout is also a free machine learning software that focuses on collaborative filtering & classification. It is an upgraded version of the Apache Hadoop Platform. The number of algorithms that Apache Mahout can support is growing with time. The cutting-edge solution uses Map/Reduce paradigms to streamline business operations. Various features of Apache Mahout are below:
- Providing expressive Scala DSL & a distributed linear algebra substructure for DL computations.
- Offers native solvers for CPUs, GPUs & CUDA accelerators.
Apache Spark MLlib
Spark is a powerful data streaming platform which provides sophisticated ML features through MLlib. It offers a compatible ML platform having multiple APIs to implement machine learning models instantly.
Some algorithms facilitated by MLlib are below:
- Classification, Naive Bayes
- Regression- Linear & Survival Analysis
- Decision Trees & Random Forests
Oryx 2 utilises Lambda Architecture for instant & large-scale ML processing. It was built on the foundation of Apache Spark architecture that facilitates rapid prototyping & applications. This also supports end-to-end model development for efficient filtering, classification & clustering operations. Oryx 2 has the following tiers:
- The first tier is a generic lambda that offers high speed and provides layers that are not unique to Machine Learning processes.
- In the second tier, there are ML abstractions for choosing hyper-parameters.
- When it comes to the third tier, there are end-to-end implementations of ML applications.
H2O’s deep learning platform offers a compatible Artificial Neural Network which is open-source with linear scalability. Moreover, it supports statistical & machine learning algorithms such as gradient-boosted machines and generalised linear models. It has various components and parameters which experts can modify based on given datasets. It comprises an adaptive learning rate that facilitates accurate predictive output.
Pytorch is a free machine learning software-based library that supports applications such as computer vision. Pytorch offers an advanced deep-learning framework. It has two essential features such as deep learning Neural Networks & Tensors. With Pytorch, consumers can create rapid prototypes for research.
RapidMiner offers an integrated platform to perform data preparations, machine learning processes, and text mining for predictive analytics. It is famous in the industry for instant revenue boost, cost reduction, and risk mitigation. It also provides cutting-edge GUI-based drag & drop features that easily build data processing workflows from 2000+ nodes.
Weka is a machine learning software that is coded in Java programming language. It comprises various machine learning algorithms that are always ready for use in data mining tasks. Some famous tools are:
- Data preparation
Weka is a free GUI interface that enables easy application of ML algorithms with less professional programming. Consequently, MI software developed by a machine learning agency is suitable for beginners in the ML field.
Konstanz Information Miner is a free data analytics, reporting & integration platform. With KNIME, experts can accomplish various components of ML & data mining. It can upgrade the database with the passage of time by integrating the latest features. This supports consumers in understanding data and designing workflows that are easily accessible.
KNIME uses a modular data pipelining concept. With the support of GUI & JDBC, it can combine various data sources to perform data modelling and visualisation without professional coding.
The Bottom Line
The use of machine learning software can help modern-day industries to design various models from scratch for instant prototyping. Industry experts can also work with third-party vendors to create multiple arrays of software applications. Hence, the significance of using machine learning software to streamline business operations has become obvious.