Top 10 TensorFlow Alternatives & Competitors

Top 10 Alternatives to TensorFlow Recently Reviewed By G2 Community

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MATLAB
By MathWorks
4.5/5
(766)
Product Description
MATLAB is a high-level programming and numeric computing environment widely utilized by engineers and scientists for data analysis, algorithm development, and system modeling. It offers a desktop environment optimized for iterative analysis and design processes, coupled with a programming language that directly expresses matrix and array mathematics. The Live Editor feature enables users to create scripts that integrate code, output, and formatted text within an executable notebook. Key Features and Functionality: - Data Analysis: Tools for exploring, modeling, and analyzing data. - Graphics: Functions for visualizing and exploring data through various plots and charts. - Programming: Capabilities to create scripts, functions, and classes for customized workflows. - App Building: Facilities to develop desktop and web applications. - External Language Interfaces: Integration with languages such as Python, C/C++, Fortran, and Java. - Hardware Connectivity: Support for connecting MATLAB to various hardware platforms. - Parallel Computing: Ability to perform large-scale computations and parallelize simulations using multicore desktops, GPUs, clusters, and cloud resources. - Deployment: Options to share MATLAB programs and deploy them to enterprise applications, embedded devices, and cloud environments. Primary Value and User Solutions: MATLAB streamlines complex mathematical computations and data analysis tasks, enabling users to develop algorithms and models efficiently. Its comprehensive toolboxes and interactive apps facilitate rapid prototyping and iterative design, reducing development time. The platform's scalability allows for seamless transition from research to production, supporting deployment on various systems without extensive code modifications. By integrating with multiple programming languages and hardware platforms, MATLAB provides a versatile environment that addresses the diverse needs of engineers and scientists across industries.
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Reviewers say compared to TensorFlow, MATLAB is:
Slower to reach roi
More expensive
Easier to admin
Categories in common with TensorFlow:
Data Science and Machine Learning Platforms

Vertex AI
By Google
4.3/5
(636)
Product Description
Vertex AI is a managed machine learning (ML) platform that helps you build, train, and deploy ML models faster and easier. It includes a unified UI for the entire ML workflow, as well as a variety of tools and services to help you with every step of the process. Vertex AI Workbench is a cloud-based IDE that is included with Vertex AI. It makes it easy to develop and debug ML code. It provides a variety of features to help you with your ML workflow, such as code completion, linting, and debugging. Vertex AI and Vertex AI Workbench are a powerful combination that can help you accelerate your ML development. With Vertex AI, you can focus on building and training your models, while Vertex AI Workbench takes care of the rest. This frees you up to be more productive and creative, and it helps you get your models into production faster. If you're looking for a powerful and easy-to-use ML platform, then Vertex AI is a great option. With Vertex AI, you can build, train, and deploy ML models faster and easier than ever before.
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Reviewers say compared to TensorFlow, Vertex AI is:
More expensive
More usable
Categories in common with TensorFlow:
Data Science and Machine Learning Platforms

IBM Watson Studio
By IBM
4.2/5
(166)
Product Description
IBM Watson Studio accelerates the machine and deep learning workflows required to infuse AI into your business to drive innovation. It provides a suite of tools for data scientists, application developers and subject matter experts to collaboratively and easily work with data and use that data to build, train and deploy models at scale.
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Reviewers say compared to TensorFlow, IBM Watson Studio is:
Slower to reach roi
More expensive
Categories in common with TensorFlow:
Data Science and Machine Learning Platforms
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Amazon SageMaker
By Amazon Web Services (AWS)
4.2/5
(48)
Product Description
Amazon SageMaker is a fully managed service that enables data scientists and developers to build, train, and deploy machine learning (ML) models at scale. It provides a comprehensive suite of tools and infrastructure, streamlining the entire ML workflow from data preparation to model deployment. With SageMaker, users can quickly connect to training data, select and optimize algorithms, and deploy models in a secure and scalable environment. Key Features and Functionality: - Integrated Development Environments (IDEs): SageMaker offers a unified, web-based interface with built-in IDEs, including JupyterLab and RStudio, facilitating seamless development and collaboration. - Pre-built Algorithms and Frameworks: It includes a selection of optimized ML algorithms and supports popular frameworks like TensorFlow, PyTorch, and Apache MXNet, allowing flexibility in model development. - Automated Model Tuning: SageMaker can automatically tune models to achieve optimal accuracy, reducing the time and effort required for manual adjustments. - Scalable Training and Deployment: The service manages the underlying infrastructure, enabling efficient training of models on large datasets and deploying them across auto-scaling clusters for high availability. - MLOps and Governance: SageMaker provides tools for monitoring, debugging, and managing ML models, ensuring robust operations and compliance with enterprise security standards. Primary Value and Problem Solved: Amazon SageMaker addresses the complexity and resource-intensive nature of developing and deploying ML models. By offering a fully managed environment with integrated tools and scalable infrastructure, it accelerates the ML lifecycle, reduces operational overhead, and enables organizations to derive insights and value from their data more efficiently. This empowers businesses to innovate rapidly and implement AI solutions without the need for extensive in-house expertise or infrastructure management.
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Reviewers say compared to TensorFlow, Amazon SageMaker is:
Slower to reach roi
More expensive
Easier to do business with
Categories in common with TensorFlow:
Data Science and Machine Learning Platforms

Anaconda Platform
By Anaconda, Inc.
4.5/5
(243)
Product Description
The Anaconda AI Platform is a unified platform for organizations looking to securely leverage open source for AI development. As the only comprehensive platform that combines trusted distribution, simplified workflows, real-time insights, and governance controls, the Anaconda AI Platform helps organizations boost practitioner productivity while reducing time, cost, and risk.
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Reviewers say compared to TensorFlow, Anaconda Platform is:
Slower to reach roi
Easier to do business with
Easier to admin
Categories in common with TensorFlow:
Data Science and Machine Learning Platforms

Altair AI Studio
By Altair
4.6/5
(509)
Product Description
RapidMiner is a powerful, easy to use and intuitive graphical user interface for the design of analytic processes. Let the Wisdom of Crowds and recommendations from the RapidMiner community guide your way. And you can easily reuse your R and Python code.
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Reviewers say compared to TensorFlow, Altair AI Studio is:
More expensive
More usable
Easier to set up
Categories in common with TensorFlow:
Data Science and Machine Learning Platforms

Google Cloud AutoML
By Google
4.1/5
(22)
Product Description
Google Cloud AutoML is a suite of machine learning products designed to enable developers with limited expertise to train high-quality custom models tailored to their specific business needs. By leveraging Google's advanced transfer learning and neural architecture search technologies, AutoML simplifies the process of building, deploying, and scaling machine learning models, making AI more accessible to a broader audience. Key Features and Functionality: - Automated Model Training: AutoML automates the selection of model architecture and hyperparameter tuning, reducing the need for manual intervention and specialized knowledge. - User-Friendly Interface: The platform offers an intuitive graphical interface that allows users to upload data, train models, and manage deployments with ease. - Versatile Model Types: AutoML supports various data types and tasks through specialized services: - AutoML Vision: For image classification and object detection. - AutoML Natural Language: For text classification, sentiment analysis, and entity recognition. - AutoML Translation: For creating custom translation models between language pairs. - AutoML Video Intelligence: For video classification and object tracking. - AutoML Tables: For structured data tasks like regression and classification. - Seamless Integration: AutoML integrates with other Google Cloud services, facilitating efficient data management, model deployment, and scalability. Primary Value and Problem Solving: Google Cloud AutoML democratizes machine learning by enabling users without deep technical expertise to develop and deploy custom models. This accessibility allows businesses to harness the power of AI to solve complex problems, such as improving customer experiences through personalized recommendations, automating content moderation, enhancing language translation services, and gaining insights from large datasets. By reducing the barriers to entry, AutoML empowers organizations to innovate and stay competitive in their respective industries.
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Reviewers say compared to TensorFlow, Google Cloud AutoML is:
More expensive
More usable
Slower to reach roi
Categories in common with TensorFlow:
Data Science and Machine Learning Platforms

Alteryx
By Alteryx
4.6/5
(671)
Product Description
Alteryx drives transformational business outcomes through unified analytics, data science, and process automation.
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Reviewers say compared to TensorFlow, Alteryx is:
More expensive
Slower to reach roi
More usable
Categories in common with TensorFlow:
Data Science and Machine Learning Platforms

Dataiku
By Dataiku
4.4/5
(188)
Product Description
Dataiku is the Universal AI Platform, giving organizations control over their AI talent, processes, and technologies to unleash the creation of analytics, models, and agents.
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Reviewers say compared to TensorFlow, Dataiku is:
Slower to reach roi
More expensive
More usable
Categories in common with TensorFlow:
Data Science and Machine Learning Platforms

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