mobi, epub |eng | 2018-12-27 | Author:Sudharsan Ravichandiran

def zero_state(self, batch_size, dtype): def expand(x, dim, N): return tf.concat([tf.expand_dims(x, dim) for _ in range(N)], axis=dim) with tf.variable_scope('init', reuse=self.reuse): state = { 'controller_state': expand(tf.tanh(tf.get_variable('init_state', self.rnn_size, initializer=tf.random_normal_initializer(mean=0.0, stddev=0.5))), dim=0, N=batch_size), 'read_vector_list': ...

epub |eng | 2019-01-31 | Author:Santanu Pattanayak

In the next section, we will go through how convolutional neural networks and the LSTM version of recurrent neural networks can be used to build an end-to-end video captioning system. ...

epub |eng | 2019-07-26 | Author:Cory Lesmeister

To be a successful data science professional you need to have math, programming skills, as well as knowledge of the business domain. As we can see, AI, data science, data ...

epub |eng | | Author:Timothy Masters

The following notation will be used: W Weight matrix, a column for each visible neuron and a row for each hidden neuron b Column vector of visible neuron biases c ...

epub |eng | 2019-08-11 | Author:Tanish Baranwal & Alizishaan Khatri & Ajay Baranwal [Tanish Baranwal]

epub |eng | 2019-09-07 | Author:Bassens Aglaé & Beyleveld Grant & Jon Krohn [Bassens Aglaé]

epub |eng | | Author:Laganiere, Robert

Clearly, the noisy pixels shifted the mean value of neighboring pixels. As a result, the noise is still visible even if it has been blurred by the mean filter. The ...

epub |eng | 2019-02-27 | Author:Giuseppe Bonaccorso; [Неизв.]

epub |eng | 2019-06-15 | Author:Emmanuel Ameisen

Dimensionality Reduction for Errors We described vectorization and dimensionality reduction techniques for data exploration in “Vectorizing” and “Dimensionality reduction”. Let’s see how the same techniques can be used to make ...

epub |eng | 2019-03-25 | Author:Alok Malik

Principal Component Analysis The next type of dimension reduction method we will cover is called PCA. This is a very common technique used by researchers in a wide variety of ...

epub |eng | 2019-04-13 | Author:Hobson Lane & Cole Howard & Hannes Hapke [Lane, Hobson & Howard, Cole & Hapke, Hannes]

epub |eng | 2017-10-27 | Author:Francois Chollet [Chollet, Francois]

Figure 6.2. Whereas word representations obtained from one-hot encoding or hashing are sparse, high-dimensional, and hardcoded, word embeddings are dense, relatively lowdimensional, and learned from data. There are two ways ...

epub |eng | 2020-01-26 | Author:Finlay, Steven [Finlay, Steven]

Artificial intelligence is most effective at supporting the automation of tasks when: Tasks are well defined. You can understand clearly what’s involved in doing it. There is lots of data ...

epub |eng | 2018-07-18 | Author:Arumugam, Rajesh; Shanmugamani, Rajalingappaa;

The second method is a smarter way of labeling words, by using neighboring tags that are made available through an approach likely similar to the first step. For example, if ...

epub |eng | 2018-09-28 | Author:Sean Saito