artificial-intelligence

问题 I'm building a RNN loosely based on the TensorFlow tutorial. The relevant parts of my model are as follows: input_sequence = tf.placeholder(tf.float32, [BATCH_SIZE, TIME_STEPS, PIXEL_COUNT + AUX_INPUTS]) output_actual = tf.placeholder(tf.float32, [BATCH_SIZE, OUTPUT_SIZE]) lstm_cell = tf.nn.rnn_cell.BasicLSTMCell(CELL_SIZE, state_is_tuple=False) stacked_lstm = tf.nn.rnn_cell.MultiRNNCell([lstm_cell] * CELL_LAYERS, state_is_tuple=False) initial_state = state = stacked_lstm.zero_state(BATCH

问题 I'm building a RNN loosely based on the TensorFlow tutorial. The relevant parts of my model are as follows: input_sequence = tf.placeholder(tf.float32, [BATCH_SIZE, TIME_STEPS, PIXEL_COUNT + AUX_INPUTS]) output_actual = tf.placeholder(tf.float32, [BATCH_SIZE, OUTPUT_SIZE]) lstm_cell = tf.nn.rnn_cell.BasicLSTMCell(CELL_SIZE, state_is_tuple=False) stacked_lstm = tf.nn.rnn_cell.MultiRNNCell([lstm_cell] * CELL_LAYERS, state_is_tuple=False) initial_state = state = stacked_lstm.zero_state(BATCH

问题 Is there any way to import a JSON file (contains 100 documents) in elasticsearch server? I want to import a big json file into es-server.. 回答1: You should use Bulk API. Note that you will need to add a header line before each json document. $ cat requests { "index" : { "_index" : "test", "_type" : "type1", "_id" : "1" } } { "field1" : "value1" } $ curl -s -XPOST localhost:9200/_bulk --data-binary @requests; echo {"took":7,"items":[{"create":{"_index":"test","_type":"type1","_id":"1","_version

问题 I've read about neural network a little while ago and I understand how an ANN (especially a multilayer perceptron that learns via backpropagation) can learn to classify an event as true or false. I think there are two ways : 1) You get one output neuron. It it's value is > 0.5 the events is likely true, if it's value is <=0.5 the event is likely to be false. 2) You get two output neurons, if the value of the first is > than the value of the second the event is likely true and vice versa. In

问题 Closed. This question is off-topic. It is not currently accepting answers. Want to improve this question? Update the question so it's on-topic for Stack Overflow. Closed 4 years ago . I'm trying to make a stock market simulator (perhaps eventually growing into a predicting AI), but I'm having trouble finding data to use. I'm looking for a (hopefully free) source of historical stock market data. Ideally, it would be a very fine-grained (second or minute interval) data set with price and volume

问题 I am confused about the terms overestimation/underestimation. I perfectly get how A* algorithm works, but i am unsure of the effects of having a heuristic that overestimate or underestimate. Is overestimation when you take the square of the direct birdview-line? And why would it make the algorithm incorrect? The same heuristic is used for all nodes. Is underestimation when you take the squareroot of the direct birdview-line? And why is the algorithm still correct? I can't find an article

问题 Closed. This question is off-topic. It is not currently accepting answers. Want to improve this question? Update the question so it's on-topic for Stack Overflow. Closed 3 years ago . I'm looking to do some sentence analysis (mostly for twitter apps) and infer some general characteristics. Are there any good natural language processing libraries for this sort of thing in Ruby? Similar to Is there a good natural language processing library but for Ruby. I'd prefer something very general, but

问题 I have an assignment to make an AI Agent that will learn play a video game using ML. I want to create a new environment using OpenAI Gym because I don't want to use an existing environment. How can I create a new, custom, Environment? Also, is there any other way that I can start to develop making AI Agent to play an specific video game without the help of OpenAI Gym? 回答1: See my banana-gym for an extremely small environment. Create new environments See the main page of the repository: https:

问题 Data loss: not an sstable (bad magic number): perhaps your file is in a different file format and you need to use a different restore operator? I'm currently training Tensorflow-wavenet with a directory of .wav audio files. Now, I want to stop the training and generate output, however the commands are not working. Here is terminal training: I have seen this stackoverflow post, but tf.train.export_meta_graph does nothing. Also, if I try to generate output in a new terminal tab, like so: cd

问题 I am developing a Tic Tac Toe version that uses different AI and ML techniques in java but I'm having some problem with slowing down the simulation. Basically I would like to see the game as if it was played by two normal player while now as soon as I run it I get the final game state. Here is my code: Board.java package com.nicolagheza.tictactoe; public class Board { // package access Cell[][] cells; // 2D array of ROWS-by-COLS Cell instances /** Constructor to initialize the game board */