SlideShare a Scribd company logo
1 of 10
7 Best AI tools in
2020
By Space-O Technologies
1. Tensorflow
● Programming language: Uses an easy-to-learn language Python
● Pros: Keeps code lean and development efficient due to simplifications and
abstractions
● Cons: It’s slow, as Python is not the fastest of languages and lacks pre-trained
models
2. Microsoft CNTK
● Programing languages: C++, C#, Java, and Python
● Pros: It is very flexible and allows for distributed training
● Cons: Implemented in Network Description Language and lacks visualization
3. Keras
● Programming language: Python
● Pros: Runs seamlessly on both CPU and GPU
● Cons: It can’t be efficiently used as an independent framework
4. Theano
● Programming language: Python
● Pros: Properly optimized for CPU and GPU and efficient for numerical tasks
● Cons: A bit buggy on AWS and needs to be used with other libraries to gain a high
level of abstraction
5. Sci-kit Learn
● Programming language: Python
● Pros: Many main algorithms are available
● Cons: Not very efficient with GPU
6. Caffe
● Programming language: C++
● Pros: Allows for the training of models without writing code
● Cons: Bad for recurrent networks and not great with new architectures
7. Torch
● Programing language: C
● Pros: Lots of pre-trained models available and very flexible
● Cons: Documentation is quite unclear and Lua is not a very popular language
Read in detail about best Ai Tools
https://www.spaceotechnologies.com/top-ai-frameworks-tools/
Thank you!
By the way, which is your
favorite AI tool?

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7 best AI tools in 2020

  • 1. 7 Best AI tools in 2020 By Space-O Technologies
  • 2. 1. Tensorflow ● Programming language: Uses an easy-to-learn language Python ● Pros: Keeps code lean and development efficient due to simplifications and abstractions ● Cons: It’s slow, as Python is not the fastest of languages and lacks pre-trained models
  • 3. 2. Microsoft CNTK ● Programing languages: C++, C#, Java, and Python ● Pros: It is very flexible and allows for distributed training ● Cons: Implemented in Network Description Language and lacks visualization
  • 4. 3. Keras ● Programming language: Python ● Pros: Runs seamlessly on both CPU and GPU ● Cons: It can’t be efficiently used as an independent framework
  • 5. 4. Theano ● Programming language: Python ● Pros: Properly optimized for CPU and GPU and efficient for numerical tasks ● Cons: A bit buggy on AWS and needs to be used with other libraries to gain a high level of abstraction
  • 6. 5. Sci-kit Learn ● Programming language: Python ● Pros: Many main algorithms are available ● Cons: Not very efficient with GPU
  • 7. 6. Caffe ● Programming language: C++ ● Pros: Allows for the training of models without writing code ● Cons: Bad for recurrent networks and not great with new architectures
  • 8. 7. Torch ● Programing language: C ● Pros: Lots of pre-trained models available and very flexible ● Cons: Documentation is quite unclear and Lua is not a very popular language
  • 9. Read in detail about best Ai Tools https://www.spaceotechnologies.com/top-ai-frameworks-tools/
  • 10. Thank you! By the way, which is your favorite AI tool?