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TensorFlow description
TensorFlow is a free and open-source software platform designed to help you build, launch, and manage machine learning applications. It offers a set of tools and resources that simplify the process of developing and training machine learning models, making it possible to apply these powerful technologies to various tasks such as image recognition, natural language processing, and predictive modeling. TensorFlow can be used in different environments, including web browsers, mobile devices, and large-scale cloud computing systems.
Who is TensorFlow best for
TensorFlow is a versatile machine learning platform ideal for developers, researchers, and data scientists building and deploying ML applications. Users praise its flexibility, pre-trained models, and ability to handle large datasets, while noting the initial learning curve and occasional documentation challenges. TensorFlow excels in image recognition, NLP, and predictive analysis, offering robust support for diverse ML tasks.
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Ideal for small, medium, and large companies seeking to develop ML applications.
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A good fit for Education and Software/IT, suitable for various other industries like Healthcare, Finance, and E-commerce.
TensorFlow features
| Supported TensorFlow supports GPU training for accelerated model training. |
| Supported TensorFlow supports building and training deep neural networks. |
| Supported TensorFlow Lite enables deploying models on Android and iOS. |
| Supported TensorFlow Lite and TensorFlow Lite for Microcontrollers enable model deployment on edge devices. |
| Supported TensorFlow supports exporting to TensorFlow Lite and other formats like TensorRT via SavedModel and ONNX. |
| Supported TensorFlow offers robust data preprocessing capabilities through TensorFlow Transform and Keras preprocessing layers. |
| Supported TensorFlow supports cloud deployment through integrations with Google Cloud and other tools. |
We evaluate the sentiment that users express about non-functional aspects of the software
Ease of Use
Reliability and Performance
Ease of Implementation
TensorFlow reviews
We've summarised 173 TensorFlow reviews (TensorFlow Capterra reviews and TensorFlow G2 reviews) and summarised the main points below.
- Flexible and adaptable for various project sizes and complexities.
- Pre-trained models and built-in support save time.
- Excellent for building and deploying machine learning models, including image recognition, NLP, and predictive analysis.
- Handles large datasets efficiently with automatic optimization.
- Strong community support and extensive resources.
- Difficult for beginners to grasp initially.
- Can be overwhelming due to complexity, especially advanced features.
- Documentation can be confusing at times, requiring external resources.
- Slower performance compared to other frameworks when training large models.
- Compatibility issues between different TensorFlow versions.
TensorFlow alternatives
neptune.aiBetter for tracking and managing machine learning experiments. Ease of use and excellent customer support are highly praised. Offers both cloud-based and self-hosted options. Is growing faster than TensorFlow. Positive pricing sentiment.Read more
Saturn CloudBetter for collaboration and cloud deployment with managed infrastructure. Easier to use with a positive pricing sentiment. Has significant momentum. Offers a free tier with GPU access. Connecting to Jupyter server can be slow.Read more
Qlik AutoMLBetter for those without data science expertise, providing automated model building and a no-code approach. Has a user-friendly interface and is growing faster. A TensorFlow competitor focused on automated machine learning.Read more
SAS Visual Data Mining and Machine LearningBetter suited for enterprise customers with existing data science teams seeking an integrated platform. More visual interface focused. Less open-source integration and more expensive than TensorFlow. Has more momentum currently.Read more
Apache UsergridBetter for mobile app backend development. Easier to use, but less reliable. Open-source and free, potentially saving costs. Limited community support. Suited for developers needing backend infrastructure.Read more
NetBeansBetter for general application development. Supports more traditional programming languages like Java, PHP, and C/C++. A good TensorFlow competitor for building desktop, mobile, and web applications.Read more
TensorFlow FAQ
What is TensorFlow and what does TensorFlow do?
TensorFlow is a free, open-source platform for building and deploying machine learning models. It offers tools and resources for developing and training models, enabling applications like image recognition and natural language processing. TensorFlow is adaptable for various project sizes and complexities and supports deployment across different environments.
How does TensorFlow integrate with other tools?
TensorFlow integrates with various tools for cloud deployment (Google Cloud, other tools), mobile deployment (TensorFlow Lite), and edge deployment (TensorFlow Lite for Microcontrollers). It also supports model exporting to formats like TensorRT via SavedModel and ONNX. It offers robust data preprocessing capabilities through TensorFlow Transform and Keras.
What the main competitors of TensorFlow?
Top TensorFlow competitors include PyTorch, Keras, scikit-learn, and XGBoost. These alternatives offer similar functionalities for building and training machine learning models, catering to various levels of expertise and project requirements. Some excel in specific areas like deep learning or simpler model deployment.
Is TensorFlow legit?
TensorFlow is a legitimate and widely used open-source machine learning platform. It's known for its flexibility and comprehensive tools, though it can be challenging for beginners. It's trusted by numerous developers for various machine learning tasks.
How much does TensorFlow cost?
TensorFlow is an open-source library and is free to use. There may be costs associated with using related Google Cloud Platform services. There is no pricing information available for TensorFlow itself.
Is TensorFlow customer service good?
TensorFlow's customer service receives mixed reviews. While the community provides strong support and training resources, some users find navigating the platform's complexities challenging and express the need for more user-friendly guides.
Reviewed by
Michal has worked at startups for many years and writes about topics relating to software selection and IT management. As a former consultant for Bain, a business advisory company, he also knows how to understand needs of any business and find solutions to its problems.
Tymon is a seasoned CTO who loves finding the perfect tools for any task. He recently headed up the tech department at Batmaid, a well-known Swiss company, where he managed about 60 software purchases, including CX, HR, Payroll, Marketing automation and various developer tools.