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Code gist for Developers. Miguel de Alba """ import json import random import requests from time import sleep from requests. GitHub only allows 60 requests per hour. So we are making less than that to avoid getting banned. To be called only once! List of strings """ for label in labels: List of strings """ for milestone in milestones: Dictionary representing an SourceForge ticket. Include a comment with the format: Labels are already migrated. Do not call this again. Milestones are already migrated.
This document attempts to clarify this. LSTM's stateful parameter is set to False. Put simply, in the forward pass, every sequence of one batch starts with its own initial state, initilizes at every batch, not just at the first batch of the training loopand mutate independently afterwards.
That is, if a batch has three samples [seq1, seq2, seq3], then the total states needed by the lstm would be: See the following code for more. This implementation is different from Keras': Their value are finals and cannot be re-assigned.
Rest parameter function student name, I recently dug into the language, and presented a brief tutorial to about 20 of my colleagues at ConsenSys. I was excited to take a look at the Vyper teams perspective on contract design, but ultimately struggled to understand many of the design decisions.
Realizing that the language is still experimental, I hope it's helpful that I share my impressions sooner than later. So there may be 'pythonic' design elements that which I misunderstand. Secondly, I will try to frame my comments with respect to the stated design goals for the language. They are very laudable goals, which are what initially attracted me to the language.
It should be possible and natural to build secure smart-contracts in Vyper. Language and compiler simplicity: The language and the compiler implementation should strive to be simple. Vyper code should be maximally human-readable. Furthermore, it should be maximally difficult to write misleading code Although it's not explicitly defined, I believe an auditable language would include: Yes, inheritance is dangerous, but code reuse can be very beneficial as well. I believe adoption will be held back by this.
Also, will 4-byte identifiers be compatible with solidity? Or is this breaking the ABI? I tried many ways, and looked at the docs, but couldn't figure out how to do this. It always got the error "Invalid top-level statement". This worked fine, and I like the comma dangle but I couldn't find anything useful to actually do with a struct.
There is support for mappings, but apparently not to a struct. For example, this works: User[address] will that eventually work? Another note about mappings: Compared to solidity, I feel it is hard to determine that we're looking at a mapping. This is pretty restrictive, but it seems like a reasonable decision given the design goals.
I like this pattern much more than Solidity's approach. They are quite readable. This class just records a 'column number' e. The 'match' method is used to compare the feature value in an example to the feature value stored in the question.
See the demo below. Compare the feature value in an example to the feature value in this question. This is just a helper method to print the question in a readable format. For each row in the dataset, check if it matches the question. If so, add it to 'true rows', otherwise, add it to 'false rows'. There are a few different ways to do this, I thought this one was the most concise. The uncertainty of the starting node, minus the weighted impurity of two child nodes.
This holds a dictionary of class e. This holds a reference to the question, and to the two child nodes. Load the R packages needed for this Gist: Existing baseline coefficient matrices must be removed first, as is done here: Baseline matrix construction config scripts. This can be done manually shown or added to the SGP package by contacting the package maintainers - https: This notebook introduces commands for getting data and for basic data cleaning and exploration, pipeline creation, model training, model persistance to Watson Machine Learning repository, model deployment, and scoring.
This notebook uses Python 3. Use the toy dataset to recognize hand-written digits. First, you need to install required packages. You can do it by running the following code. Run it only one time. Support Vector Machines with radial basis function as kernel is used in the following example. A pipeline consists of transformers and an estimator.
For simplicity of this example tuning section is omitted. Put authentication information from your instance of Watson Machine Learning service here. The MLRepositoryArtifact method expects a trained model object, training data, and a model name. It is this model name that is displayed by the Watson Machine Learning service. You have already learned how save and load the model from Watson Machine Learning repository. To do that you can use the following sample code: To do that, execute the following sample code: You learned how to use scikit-learn machine learning as well as Watson Machine Learning for model creation and deployment.
This notebook and its source code are released under the terms of the MIT License. Prefetch and load your main content via ajax. Use CSS3 transitions, true or false transition: Speed of the transition, in milliseconds label: Label for the navigation toggle insert: Insert the toggle before or after the navigation customToggle: Close the navigation when one of the links are clicked openPos: Position of the opened nav, relative or static navClass: If changed, you need to edit the CSS too!