python 代写

Python是一种高级编程语言,它用于创建网页,移动应用程序,脚本和机器学习模型。它拥有强大的类库,允许开发人员快速编写功能强大的应用程序。

Python有许多优点,其中包括:它是相对容易学习和使用的动态编程语言;它拥有丰富的内置库和模块;它拥有广泛的社区支持;它支持跨平台;它可以进行快速原型开发;它可以有效地利用内存;它可以使用C / C ++扩展;它支持大量的开源框架和库;它具有强大的编程能力和可读性;它支持多种编程风格;它可以进行测试驱动开发,以及其他许多优点。

HW

Kraken API 您将创建两个单独的程序(python,C / C++,ruby,Golang或其他程序),报告来自流行的加密货币交换服务器(称为Kraken)的返回消息。请注意,绝对没有必要花钱。您的程序将仅返回您的钱包余额和另一个信息,其中这些请求需要特殊密钥来加密/解密/验证。本练习将向我们展示如何使用加密密钥和HTTP协议,发送格式正确的数据包。任何格式不正确的消息都不会通过到服务器的完整性检查。 转到 https://www.kraken.com/。 如果您还没有登录帐户,请创建它。然后登录。 转到 https://www.kraken.com/u/security/api ->添加密钥。创建您的 API 密钥和密钥。 只留给自己!您将需要这些 API 密钥才能继续。 现在你已经准备好了。 重要提示:考试后删除您的 API 密钥。 程序应显示以下两个请求的响应消息: A. API 文档 -> REST API ->钱包 -> 获取余额 (https://docs.kraken.com/rest/#tag/User-Data/operation/getAccountBalance) 您的余额应该是空的,假设您在Kraken没有任何硬币或金钱。 显示此 API 调用的返回消息。 B. API 文档 -> REST API -> 下订单 (https://docs.kraken.com/rest/#tag/User-Trading/operation/addOrder) 仅发送“卖出”订单。同样,任何市场符号都可以。 显示此 API 调用的返回消息。 要完成A和B,请参阅 https://docs.kraken.com/rest/#section/Authentication。但是,您需要将此示例代码与密钥和机密相结合。然后,您将能够向服务器发送经过验证的“http请求”消息。仔细阅读 API 文档。请勿使用现有的库,如CCXT或任何其他与Kraken相关的库。 **任务 1:在 python […]

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CS 131 Project 1 Brewin Interpreter

Introduction In this project, you will be implementing a simple interpreter for a new programming language, called Brewin. Brewin is an object-oriented variant of the LISP language. You guessed it – that means there are lots of parentheses! :^) You¡¯ll be implementing your interpreter in Python. This project is the first of three – in

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COMP90054 Assignment 3 Azul Project

Assignment 3: Azul Project You must read fully and carefully the assignment specification and instructions detailed in this file. You are NOT to modify this file in any way. Course: COMP90054 AI Planning for Autonomy @ Semester 1, 2023 Instructor: Tim Miller and Nir Lipovetzky Deadline Team Registration: Monday 1 May, 2023 @ 18:00 (start

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step functions

step_functions Using Step Functions to Orchestrate Massively Parallel Batch Jobs¶ You’ll recall from our serverless demonstration a couple of weeks ago, that we can upload Lambda functions programmatically: import boto3 import json import time import requests from concurrent.futures import ThreadPoolExecutor import matplotlib.pyplot as plt # Access our class IAM role, which allows Lambda # to

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cs585 HW5 ML

Total points: 6 (+1… the total will be capped at 6) This last hw is on supervised machine learning! As you now know, it’s data-related (lots, and lots, and lots of it), after all 🙂 Here is a summary of what you’ll do: on Google’s Colab, train a neural network on differentiating between a cat

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cs585 HW5 Data mining

HW5: Data Mining [tool-based] Total points: 6 Summary: In this homework, you are going to use three UI-based tools (no coding!), to carry out data mining: WEKA, KNIME, RapidMiner (the last two are dataflow-driven!). There are 3 questions you need to answer about linear regression, one using each tool. Description WEKA Start by downloading WEKA,

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COMP3620 6320 Artificial Intelligence

“””Inference functions used with backtracking search. COMP3620/6320 Artificial Intelligence The Australian National University Authors: COMP-3620 team Date: 2022 Student Details ————— Student Name: Student Number: import collections from typing import Callable, Dict, List, Optional, Tuple from csp import CSP Assignment = Dict[str, str] Pruned = List[Tuple[str, str]] def forward_checking(var: str, assignment: Assignment, gamma: CSP) ->

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COMP3620 6320 Artificial Intelligence

“””Heuristics for variable selection and value ordering. COMP3620/6320 Artificial Intelligence The Australian National University Authors: COMP-3620 team Date: 2022 Student Details ————— Student Name: Student Number: This is where you need to write your heuristics for variable selection and value ordering. from typing import Callable, Dict, List, Optional from csp import CSP Assignment = Dict[str,

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