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Some of the next articles are maybe not open access.
2020
TensorFlow is an end-to-end open source platform for developing and deploying machine learning applications. We can call it the complete machine learning (ML) ecosystem. All of us have seen face tagging in our photos on Facebook. Well, this is a machine learning application. Autonomous cars use object detection to avoid collisions on the road. Machines
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TensorFlow is an end-to-end open source platform for developing and deploying machine learning applications. We can call it the complete machine learning (ML) ecosystem. All of us have seen face tagging in our photos on Facebook. Well, this is a machine learning application. Autonomous cars use object detection to avoid collisions on the road. Machines
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2019
This chapter focuses on how we can leverage TensorFlow 2.0 for computer vision. There has been much breakthrough research and development in the field of computer vision, thanks to deep learning. In this chapter, we will start with a brief overview of image processing and move on to one of the most successful algorithms in computer vision, the ...
Pramod Singh, Avinash Manure
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This chapter focuses on how we can leverage TensorFlow 2.0 for computer vision. There has been much breakthrough research and development in the field of computer vision, thanks to deep learning. In this chapter, we will start with a brief overview of image processing and move on to one of the most successful algorithms in computer vision, the ...
Pramod Singh, Avinash Manure
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2018
In this chapter, you will create chatbots by using TensorFlow. You’ll start by learning some TensorFlow basics.
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In this chapter, you will create chatbots by using TensorFlow. You’ll start by learning some TensorFlow basics.
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2018
This chapter covers the basics of TensorFlow, the deep learning framework. Deep learning does a wonderful job in pattern recognition, especially in the context of images, sound, speech, language, and time-series data. With the help of deep learning, you can classify, predict, cluster, and extract features. Fortunately, in November 2015, Google released
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This chapter covers the basics of TensorFlow, the deep learning framework. Deep learning does a wonderful job in pattern recognition, especially in the context of images, sound, speech, language, and time-series data. With the help of deep learning, you can classify, predict, cluster, and extract features. Fortunately, in November 2015, Google released
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2017
In this chapter we will cover Tensorflow which allows users to define mathematical functions via computational graphs and to compute their gradients. Tensorflow is conceptually similar to Theano, and Keras uses both of them as back ends.
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In this chapter we will cover Tensorflow which allows users to define mathematical functions via computational graphs and to compute their gradients. Tensorflow is conceptually similar to Theano, and Keras uses both of them as back ends.
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TensorFlow Recognition Application
2018Building a DL model such as CNN from scratch using NumPy as we did helps us have a better understanding of how each layer works in detail. For practical applications, it is not recommended to use such implementation. One reason is that it is computationally intensive in its calculations and needs efforts to optimize the code.
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