epub |eng | 2019-03-22 | Author:Nitin Gaur

Participants are agents Our examination of participant types shows us that they all have one thing in common—they have a significant degrees of agency—they actively do things. Although systems and ...

epub, pdf |eng | 2019-03-30 | Author:Christopher Rafter [Rafter, Christopher]

Problems that could fall into either category (“Uh. I’ll need to get back to you.”) Partial or incomplete values Duplicates These are general guidelines, nothing with data is ever absolute. ...

epub |eng | 2019-10-24 | Author:Anurag Srivastava

To activate this adaptive replica selection, the following setting needs to be changed to true: cluster.routing.use_adaptive_replica_selection We can change the preceding setting through a query as well. The following code ...

epub |eng | 2019-09-27 | Author:Ian Pointer

start_time = time.process_time() b.__getitem__(33) end_time = time.process_time() end_time - start_time >> 0.0031465259999094997 Obtaining an element from this dataset takes roughly the same time as in our original audio-based one, so ...

epub |eng | | Author:By Filip Babić & By Nishant Srivastava

Create a channel with default — i.e., 0 capacity. Set up the producer. Send data in the channel. Conditional check, if the current item is equal to value Pear. Signal ...

epub |eng | 2019-06-23 | Author:Javier Luraschi

Figure 8-1. Spark processing raw data from a data lakes, databases, and data warehouses To support a broad variety of data sources, Spark needs to be able to read and ...

epub |eng | 2018-12-27 | Author:Alvaro Fuentes [Alvaro Fuentes]

epub |eng | 2019-09-03 | Author:Matt Harrison

>>> from yellowbrick.model_selection import ( ... ValidationCurve, ... ) >>> fig, ax = plt.subplots(figsize=(6, 4)) >>> vc_viz = ValidationCurve( ... RandomForestClassifier(n_estimators=100), ... param_name="max_depth", ... param_range=np.arange(1, 11), ... cv=10, ... n_jobs=-1, ...

epub |eng | 2019-09-12 | Author:Seth Weidman

mnist_soft = NeuralNetwork( layers=[Dense(neurons=89, activation=Tanh(), weight_init="glorot", dropout=0.8), Dense(neurons=10, activation=Linear(), weight_init="glorot")], loss = SoftmaxCrossEntropy(), seed=20190119) and training the model with the same hyperparameters as before (exponential weight decay from an initial ...

epub, pdf |eng | 2018-10-30 | Author:Alex Galea [Alex Galea]

Note The apply method is great because it can solve a variety of problems and allows for easily readable code. Often though, vectorized methods such as pd.Series.str can accomplish the ...

epub |eng | 2018-07-30 | Author:Devin Knight

One of the benefits of creating explicit measures is the ability to centralize formatting. Once the measure has been created, navigate to the modeling ribbon and change the formatting to ...

epub |eng | 2019-07-31 | Author:George Kyriakides

Errors and differences for gradient boost regression For the classification example, we use the hand-written digit classification dataset. Again, we define the n_estimators and learning_rate parameters: # --- SECTION 1 ...

epub |eng | 2019-03-28 | Author:David Spiegelhalter

I know of scarcely anything so apt to impress the imagination as the wonderful form of cosmic order expressed by the ‘Law of Frequency of Error’. The law would have ...

epub, azw3, pdf |eng | 2019-09-02 | Author:David Spiegelhalter

I know of scarcely anything so apt to impress the imagination as the wonderful form of cosmic order expressed by the ‘Law of Frequency of Error’. The law would have ...

epub |eng | 2018-11-29 | Author:Suresh Kumar Mukhiya & Tao Wei & James Lee [Suresh Kumar Mukhiya]