Best machine learning software — Machine learning (ML) is one strong interdisciplinary area that deals with a lot of probability, algorithms, and statistics. It is more focused at extracting data and giving comprehensive insights that can be used to create effectively working apps.
Machine Learning is an important branch of Artificial Intelligence that has proven to provide an excellent way to increase client experience and optimal automation. So in this article, I have made a list of the top 20 best machine learning software that should help your machine learning aspirations come to life.
Top 20 Best Machine Learning Softwares
- Tableau
- PyTorch
- Apache Mahout
- Keras
- Shogun
- RapidMiner
- Neural Designer
- Scikit-learn
- KNIME
- Spell
- TensorFlow
- IBM Watson Studio
- Amazon Lex
- Microsoft Azure Machine Learning
- OpenNN
- Auto-WEKA
- Datawrapper
- Google Cloud AutoML
- Amazon Machine Learning
- MLJAR
1. Tableau
Tableau is one of the best visual analytics software that is focused on transforming the way data is applied to get results out of heaps of information. It also aids in the discovery and supervision of data with great speed. It also supports distribution of perceptive information that is able to bring in improved productivity.
Features
- Secure, flexible, and comprehensive
- Helps users recognize and envision data
- Seamless creation of graphs, maps, charts, etc.
- Real-time data analytics
- Robust and interactive graphics and security
- Data blending and collaboration
2. PyTorch
PyTorch is one of the best and most popular machine learning frameworks that relies on the Torch library. This software is open-source and free to use. It can be used in places like NLP, deep learning research, computer vision, etc. Plus, it can be used to quicken the procedure between research prototyping and deployment.
Features
- Neural networks
- Ideal for deep learning research with faster speed and convenience
- Can be utilized better on cloud platforms
- Easily accessible and offers a dynamic graph
- Provision to alter network performance instantly
- Ample tools, libraries, and documentation to support
3. Apache Mahout
Apache Mahout is one of the best software great for creating efficient machine learning applications. This software has a distributed linear algebra framework that can help you implement your algorithms while letting you have access to a large range of Java libraries for different algorithms and statistical functions.
Features
- Effective for implementing scalable algorithms
- Vector and matrix libraries
- Offers support for different backend frameworks
- Executes on top of Apache Hadoop
- Ready-to-use framework for data mining
- Creates applications with clustering, filtering, etc.
4. Keras
Keras is one of the best lightweight Python-based software that is great for deep learning. It has quick prototyping features for machine learning-driven algorithms. With this software, you can execute on the top of other software tools like Theano, CNTK, TensorFlow, etc.
Features
- Fast neural network implementation
- High-level interface
- Executes with ease on CPU and GPU
- Supports almost all models of neural network
- Large community support
- User-friendly and faster deployment
5. Shogun
Shogun is one of the best open-source and free machine learning software tools that has tons of machine learning methods. It supports many data structures and algorithms that can aid you in creating high-quality machine learning programs.
Features
- Kernel-based algorithms
- Full implementation of Hidden Markov models
- Complete support for the usage of pre-calculated levels
- Designed to handle huge datasets
- Works on interfaces with different languages like C#, Python, etc.
- Well organized implementation of algorithms
6. RapidMiner
RapidMiner is another good open-source data science software worth mentioning. This software offers an understandable infrastructure to aid you prepare data, and support deep learning, machine learning, predictive analytics, and text mining. It also lets you create predictive models quickly.
Features
- Visual data science workflow designer
- Easy to use and create varied analytics
- Faster to design ML models
- End-to-end data science platform
- No-code development platform for data mining
- Provision to import own datasets
7. Neural Designer
Neural Designer is one of the best and most popular code-free Artificial Intelligence platforms and Machine Learning software out there. It is based on neural networks and has a graphical user interface that helps to simplify data entry and result interpretation. It is user-friendly and great for data science and Machine Learning.
Features
- Implementation of deep architecture with different layers
- Mathematical expressions to be exported to various computer languages
- Effective memory management for huge data sets
- Great management of data processing outcomes
- Deals effectively with issues related to parameter optimization
- Faster computations with GPU and CPU optimization
8. Scikit-learn
Scikit-learn is one of the best open-source machine learning software in Python. This software is easy-to-use and open to everyone and can be used in different contexts. It has amazing tools that handle predictive data analysis perfectly.
Features
- Apt for solutions having limited time and resources
- Especially meant for machine learning-based solutions
- Part of predictive modeling aspects and solutions
- Linear and logistic regression
- Support Vector Machines (SVM)
- Possesses inbuilt datasets like iris dataset, house prices dataset, etc.
9. KNIME
KNIME is an open-source machine learning software great for integration, BI, analytics, data reporting, and data mining. This piece of software is widely used in various industries, such as pharmaceuticals, finance, engineering, etc. It stands out as one of the few software that is easy to learn and install.
Features
- Free, open-source, and easy to learn
- Seamless integration of code of Java, C, R, Python, etc.
- Intuitive user interface
- Sophisticated data handling
- Well-defined API for plug-in extension
- Competence to create visual data flow
10. Spell
Spell is one of the best and popular machine learning operations (MLOps) platforms great for deep learning applications in changing environments. It is an great for creating and implementing machine learning projects that are meant to handle the requirements of deep learning stakeholders on-premises or cloud-based.
Features
- Effective command-line interface
- Supports simplistic and easy to use commands
- Infrastructure automation with an extensible platform
- Operates on all types of platforms
- Reduces redundancy and improves teamwork
- Lessens costs and time to value
11. Google TensorFlow
TensorFlow is one of the best and most popular open-source frameworks developed by Google. This software is outstanding and flexible for deep neural network research especially for large-scale applications. It offers simple visualization of neural networks and performs numeric calculations with graphs.
Features
- Usable across multiple platforms and devices
- Works well for research and machine learning activities
- Helps in creating neural networks and ML model
- Offers multiple abstraction levels for choosing apt resources
- Free to use and easy to deploy and train
- Fast iteration and intuitive debugging
12. IBM Watson Studio
IBM Watson is one of the best and effective machine learning frameworks that manipulates data to have deep learning and machine learning models for production use. It is one of the highest recommended for creating machine learning apps using API connections.
Features
- Empowers data scientists to manage and execute AI models
- Syncs well with other open-source frameworks like TensorFlow etc.
- Automates AI lifecycle and fastens the entire process
- Supports NLP, visual recognition and Blockchain processes
- Streamlines the deployment of ML models
- Easy combination of visual data science with open-source libraries
13. Amazon Lex
Amazon Lex is one of the best secure, comprehensive, and simple machine learning frameworks that is focused on handling deep learning issues like language perception, and speech and text recognition, etc. And when it comes to backend integration, this software has a strong integration with AWS Lambda.
Features
- Good quality speech recognition and natural language processing
- Easy management of context across conversations
- Multi-turn conversations and dialogues
- Single-click deployment for various platforms
- Streaming of natural conversations
- Seamless integration with other technology frameworks
14. Microsoft Azure Machine Learning
Microsoft Azure Machine Learning is one of the best and most popular software used for the creation and deployment of Artificial Intelligence and Machine Learning models quickly and effectively. With this software, you can create machine models with top-level quality and efficacy.
Features
- Well defined pre-trained models
- Free trial versions
- Useful for developers with limited coding experience
- Robust suite of product add-ons
- Flexible and easy building interface
- Fast and simple implementation of web services
15. OpenNN
OpenNN is great at implementing neural networks and offers the features of downloading its whole library for free from credible sources like GitHub. It is one of the best general-purpose and open-source Artificial Intelligence and Machine Learning software that can be used to rectify predictive analytical activities in many sectors like energy, engineering, and many more.
Features
- Solves many real-world applications in health, energy, etc.
- Sophisticated algorithms and utilities to manage solutions
- Predictions about the future
- Pattern assignment to different categories
- High-capacity data set loading
- Faster training and higher productivity
16. Auto-WEKA
Auto-WEKA is great at data mining and it takes care of the selection of machine learning algorithms simultaneously instead of doing it one after the other. This software is one of the best at offering a completely automated approach in the latest innovative ways.
Features
- Automated model selection
- Hyperparameter optimization
- Maximized performance and productivity
- Easily accessible to end-users
- Fully automated approach
- Helps novices in effectively identifying ML algorithms
17. Datawrapper
Datawrapper is user-friendly and an open-source machine learning software that is best used for the creation of interactive charts, graphs, maps, etc. With this software, you can extract the maximum value out of data that can be availed in any machine learning model.
Features
- Availability of different color options
- Export facility for different file formats
- Live chart update facility
- Faster creation of interactive charts
- Online access or can be installed on the server
- Data inputs through CSV or direct input
18. Google Cloud AutoML
Google Cloud AutoML is one of the best suite of machine learning products. This software lets you create effective machine learning models with beginner-level experience. The user interface is simple, intuitive and works efficiently which aids you to store data in the cloud easily.
Features
- Offers ML model training, predictive modeling, and deep learning
- Can be easily used for training complicated models
- Independent or combined use of the two services
- Ideal for use by enterprises for jobs like faster response to emails etc.
- Utilizes the power of AI in business activities
- Natural language processing, speech to text, and vice versa
19. Amazon Machine Learning
Amazon Machine Learning is great at helping developers discover patterns in data using various algorithms and mathematical models. It is one of the best software for creating machine learning-based apps.
Features
- Identifies patterns and creates mathematical models
- Offers support for different types of models
- Helps in retrieving predictions with real-time APIs
- Easy handling of large datasets with many servers
- Customizable and easy to update
- Strong auto-scaling server availability
20. MLJAR
MLJAR is one of the best for prototyping, implementing pattern recognition algorithms, and development. This software does a good job at saving time and strives to offer the best outputs.
Features
- Saves time and efforts
- Python-based package
- Works well with tabular data
- Automatic detection of data type
- No preprocessing required
- Handles appropriate missing values
Conclusion
As the years go on, we are constantly witnessing a rapid rise in the adoption of Machine Learning and Artificial Intelligence in many industries all around the world. With expert programming techniques, programmers have constantly made computers that would have the competence to learn without being programmed to do so. And with some of the best machine learning software as a guide, this dream can be birthed.
Frequently Asked Questions
The best language for Machine Learning is Python.
Machine Learning (ML) is a subset of Artificial Intelligence (AI) and has a limited scope when compared to AI that is much broader.
If you don’t have a good background in computer and/or mathematics, Machine Learning may be hard for you.
References
- Ubuntupit.com – The 20 Best AI and Machine Learning Software and Frameworks
- Spec-india.com – Top 20 Machine Learning Tools Rising In Popularity In 2022
- Trustradius – Machine Learning Tools
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