azw3, epub, pdf |eng | 2020-06-18 | Author:Foster, Matt [Foster, Matt]

epub |eng | 2020-04-29 | Author:Rob Thomas

The Challenges of Collecting New Sources of High-Volume Unstructured Data Managing data that arrives in real time requires new kinds of tools, such as Apache Kafka, which facilitates streaming data ...

epub |eng | 2019-04-30 | Author:Yuxi (Hayden) Liu [Yuxi (Hayden) Liu]

_, lossT, accT = sess.run([modelGraph.train, modelGraph.loss, modelGraph.avgAccuracy], feed_dict = {modelGraph.x: batchX, modelGraph.y: batchY, modelGraph.keepProb: modelGraph.dropOut}) print('Epoch: '+str(epoch)+' Minibatch_Loss: '+"{:.6f}".format(lossT)+' Train_acc: '+"{:.5f}".format(accT)+"\n") if epoch % 10 == 0: saver.save(sess, modelGraph.savePath) The ...

epub |eng | 2019-05-30 | Author:Karthik Ramasubramanian and Jojo Moolayil

Reduce the number of distinct locations in the variable. This can be done by tagging all the locations that are not a part of the location_list list as Others:df_new$new_location <- ...

epub |eng | 2018-08-27 | Author:Iffat Zafar [Leonardo Araujo]

Fast R-CNN In 2015, Fast R-CNN was proposed to remedy the speed problems of R-CNN. In this method, the main change is where we get proposal regions in the pipeline. ...

mobi, epub |eng | 2020-05-09 | Author:Nicolò Valigi & Gianluca Mauro

Figure 6.5 Embeddings of three T-shirts represented on a 2-D plane. T-shirts A and B are similar, so their embeddings are close. T-shirt C is different from A and B, ...

azw3 |eng | 2019-12-11 | Author:Ivan Vasilev [Vasilev, Ivan]

epub |eng | 2019-12-12 | Author:Ivan Vasilev

epub |eng | 2020-03-30 | Author:Paolo Perrotta [Paolo Perrotta]

epub |eng | 2020-05-04 | Author:Paul Zikopoulos & Rob Thomas [Paul Zikopoulos]

epub |eng | 2019-01-31 | Author:Dipayan Sarkar [Dipayan Sarkar]

Getting ready In this example, we use a dataset from the UCI ML repository on credit card defaults. This dataset contains the following information: Default payments Demographic factors Credit data ...

epub, pdf |eng | 2019-06-12 | Author:Tommaso Teofili [Tommaso Teofili]

Chapter 5. Ranking search results with word embeddings This chapter covers Statistical and probabilistic retrieval models Working with the ranking algorithm in Lucene Neural information retrieval models Using averaged word ...

epub, mobi |eng | 2019-08-12 | Author:Ajay Baranwal [Ajay Baranwal]

Technical requirements It's assumed that readers of this chapter and this book know the basics of machine learning, neural networks, and deep neural networks. Also, as a prerequisite, it's assumed ...

epub |eng | 2019-01-31 | Author:Dr. Christine Corbett Moran; [Dr. Christine Corbett Moran]

Now, imagine the government gets together and implements new legislation in which there are thirty different possible documents, which means 230 = 1,073,741,824 possible combinations and which the formula to ...

epub |eng | 2019-08-30 | Author:Brindha Priyadarshini Jeyaraman, Ludvig Renbo Olsen,
 and Monicah Wambugu

Figure 5.1: Datasets Linear Regression When performing linear regression, we are trying to find linear relationships between variables. Suppose we have a cat shelter and want to know how many ...