10 Best Machine Learning Software of 2022

Last updated on by Editorial Staff
List of the Best Machine Learning Software

You may hear a lot about machine learning lately, and you’re keen to learn more, but where do you start?

Even though you have experience with machine learning, many software options are available, and choosing from them can be challenging.

In this blog post, we’ll give you an overview of the ten best machine learning software options that helps you to make an informed decision about which is right for you.

What is Machine Learning software?

Machine learning software is artificial intelligence (AI) software that enables computers to learn from data without being explicitly programmed. Instead, it provides algorithms, APIs (application programming interfaces), and tools to allow developers to create software. 

Typical ML software applications include image recognition, predictive maintenance, fraud detection, and demand forecasting.

Here is the list of the ten best ML software tools

1. Scikit learn

Scikit-learn is an open-source machine learning library for python language. It contains various algorithms for data mining and predictive modeling, including support for deep learning and artificial neural networks. It has been used in several real-world applications, including predicting the outcomes of elections and detecting fraudulent credit card transactions.

Webpage of scikit-learn

Features

  • Classification
  • Regression
  • Clustering
  • Preprocessing
  • Model selection
  • Dimensionality reduction
Demo page of scikit learn

Our opinion

Scikit-learn is a powerful machine learning software widely used in the industry. It is open-source and free to use, making it a popular choice for beginners. However, it is also powerful enough to be used in more complex applications.

PricingThis software is entirely free
PlatformLinux, Mac OS, Windows
Programming languagesPython, Cython, C, C++

Like

  • It provided good documentation that helps to apply algorithms when you stuck
  • It provides an inbuilt dataset for practices

Dislike

  • Deep learning algorithms not available
  • The clip is not elaborative

2. TensorFlow

TensorFlow is one of the most popular free open source software libraries for machine learning and data science. It provides various deep-understanding tools, including neural networks, convolutional nets, and recurrent networks. TensorFlow also supports reinforcement learning and generative adversarial networks.

Web page of TensorFlow

Features

  • Symbolic math library
  • Dataflow programming library
  • Differentiable programming
  • Statistical machine learning
 Demo page of Tensorflow

Our opinion

TensorFlow is an excellent choice for people who want to learn more about machine learning. Additionally, TensorFlow is supported by a large community of developers, so you can find help if you need it.

PricingIt is entirely free.
PlatformLinux, Mac Os, Windows
Programming languagesPython, C++, CUDA

Like

  • Easy to install
  • Provides more resources that help to learn

Dislike

  • It does not provide control flow operations and loop functions

3. Anaconda

Anaconda is one of the most famous Python data science platforms. It has many data analytics, machine learning, and scientific computing features.

 Webpage of Anaconda

Features

  • Predictive modeling
  • Deep learning models
Distribution Demo page of Anaconda

Our opinion

Anaconda is easy-to-use software with many features that make it an excellent option for you to get into machine learning.

Pricing

It offers a free version.

The professional plan starts at $149 per year.

You need to contact the vendor to get pricing details for the business and enterprise plans.

Pricing of Anaconda
PlatformMac, Windows, Linux
Programming languagePython

Like

  • The free version is available with basic features
  • Allows you to create multiple virtual environments

Dislike

  • It is not easy to use at the beginning
  • Start-up time is low

4. PyTorch

PyTorch is open source software for machine learning libraries based on the Torch library. It offers various features such as support for multiple processors, integrated graphics processing units, and a wide range of applications. Additionally, it is available on both Windows and Linux operating systems.

Overview of PyTorch Webpage

Features

  • Autograd Module
  • Optim Module
  • NN Module
Demo page of PyTorch

Our opinion

PyTorch’s open source platform gives you the freedom to implement your ideas and experiment with them quickly. This is one of the main reasons many experts consider it the best ML software. Apart from that, PyTorch also provides excellent documentation and tutorials which can help you get started quickly.

PricingIt is entirely free of cost.
PlatformLinux, Mac Os, Windows
Programming languagePython, C++, CUDA

Like

  • It is an optimized framework for deep learning
  • It provides good documentation

Dislike

  • Not suitable for a small amount of data
  • Integrate with another application is difficult

5. Weka

Weka is a software suite containing a variety of tools for data mining, including machine learning, preprocessing, classification, regression, visualization, and more. It is open-source software released under the GNU General Public License. In addition, Weka is written in Java, so it can run on any platform that supports Java.

Overview of Weka Webpage

Features

  • Data preparation
  • Classification
  • Regression
  • Clustering
  • Visualization
Demo page of Weka

Our opinion

Weka is open-source, free-to-use software and has various features. It also has a very active community, so you can get help if you need it.

PricingIt is entirely free
PlatformLinux, Mac OS, Windows
Programming languageJava

Like

  • Provides free online courses
  • Students can easily understand the software

Dislike

  • Documentation is very less

6. Google cloud AI platform

Google’s cloud AI platform is a cloud-based comprehensive suite of tools for data analysis, machine learning, and deep learning. In addition, it provides components like training, prediction, and data labeling services.

Overview of Google Cloud Web page

Features

  • A unified UI for all ML workflow
  • Pre-trained APIs for vision, video, natural language
  • End-to-end integration
  • Support for all open-source frameworks
  • Free built algorithms
Overview  Algorithms
Overview of google cloud AI platform

Our opinion

Google Cloud AI Platform offers excellent flexibility and scalability. It supports open-source frameworks. Additionally, it provides pre-trained APIs for vision, video, and natural language processing, making it a perfect choice for deep learning applications.

Pricing

  • You need to contact the vendor to get a quote
  • A free trial is available
  • Customers will get $300 in free credits and 20+ products for free
Google Cloud Pricing
Programming languageJava, C, Python
Front-end languages like HTML, CSS, Javascript

Like

  • The user interface is easy to use
  • You can create new MI models easily
  • All AI services are available in machine learning model training

Dislike

  • UI navigation is challenging
  • No frequent updation of training and document resources

7. Amazon Personalize

Amazon Personalize is a machine learning tool that allows you to train, deploy and manage your custom machine learning models. It offers a wide range of features and flexibility, making it a perfect choice for businesses of all sizes.

Overview of Amazon Personalize Webpage

Features

  • Automatic loading and inspection of data
  • Allows you to select the correct algorithm
  • Provides accurate metrics
Overview of Amazon Personalize Dataset group dashboard

Our opinion

Amazon Personalize is a machine learning software offered by Amazon. It is a part of Amazon Web Services, allowing developers to train and deploy machine learning models.

Amazon Personalize is an excellent tool for businesses that want to take advantage of machine learning without investing much in their infrastructure. It is also very easy to use, making it a good choice for businesses with little experience with machine learning.

PricingA free trial is available
It does not offer a minimum fee or upfront fee
Using its pricing calculator, you can estimate your price
Languages support Spanish, German, French, Portuguese, Chinese, and Japanese

Like

  • It is very easy to use for newcomers

Dislike

  • Sometimes the program will be very slow

8. Apache Mahout

Apache Mahout is a distributed machine learning framework. It is used to build machine learning applications and includes several clustering, classification, and collaborative filtering algorithms.

Overview of Apache Mahout Webpage

Features

  • Distributed linear algebra
  • Classification
  • Clustering
  • Regression
  • Preprocessors
 Demo Page of Mahout

Our opinion

Apache Mahout is a top machine learning software for predictive analytics, Collaborative Filtering, Clustering, and Frequent Pattern Mining. It offers an extensive suite of data mining algorithms and the ability to create custom algorithms. Mahout also provides a platform for deploying machine learning applications.

PricingIt is entirely free.
PlatformCross-platform
Programming languageJava, Scala

Like

  • It is scalable machine learning libraries

Dislike

  • The visualization part is not so good
  • Unavailability of scientific calculation libraries

9. Amazon Sagemaker

Amazon SageMaker is a machine learning platform enabling you to quickly build, train, and deploy models at scale. It makes it easy to choose the correct algorithm and framework, get your data ready, and configure your deployment model.

Overview of  Amazon Sagemaker Webpage

Features

  • Predictive modeling
  • Visualization
  • Model Training
  • ML algorithm library
Demo page of Amazon Sagemaker

Our opinion

Amazon Sagemaker is easy to use and has a lot of capabilities that make it a powerful choice for businesses or individual users who want to get started with machine learning.

PricingA free version is available
Contact the vendor to get more information
Programming languagePython, JavaScript, Ruby, Java

Like

  • Helps small projects by reducing the time with ML models
  • No need to have prior knowledge while working with it
  • Has user-friendly interface

Dislike

  • Fewer customization options

10. H2O.ai

H2O.ai is an open-source machine learning software tool. It is best suited for enterprises for fraud detection and advanced analytics.

Overview of H2O.ai Webpage

Features

  • Ml algorithm library
  • Model training
  • Natural language processing
  • Visualization
  • Statistical modeling
  • Predictive Modeling
  • Document classification
Demo page H20.ai

Our opinion

H2O.ai offers excellent features and user experience. In addition, the company is strongly committed to its community and continuously updates its software with new features and bug fixes. Overall, H2O.ai is an excellent choice for anyone looking for machine learning software.

PricingNo free version; for pricing details, contact the vendor.
PlatformWindows
Programming languageR, Python

Like

  • It runs on low memory

Dislike

  • Lack of accountability and management

FAQs

What are the types of Machine Learning?

Three types of machine learning are supervised, unsupervised, and reinforcement learning.
Supervised learning is where the computer is given a set of training data and is then taught how to make predictions.
Unsupervised learning is where the computer is given data but not told what to do with it, and it must learn from the data itself.
Reinforcement learning is where the computer is given a set of rules and must learn from its own experience to optimize its performance.

What are some popular Machine Learning algorithms?

There are many popular machine learning algorithms, but some of the most common include support vector machines, decision trees, and artificial neural networks. 

Conclusion

Every ML software is constantly evolving and changing. As new versions are released, different software becomes the best option for various purposes.

We will update the list of the ten best ML tools we’ve provided to ensure you have the most accurate information possible. We highly recommend that you check back often to see if any changes in the best machine learning software of 2022.

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