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通过我们的数据科学教程推动您的数据职业发展。我们将带您一步步完成具有挑战性的 数据科学函数与模型。
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Deploy your Facebook Messenger Bot with Python
A step-by-step guide to easily deploying a Facebook Messenger chatbot with Python, using Flask, requests and ngrok.
Alan Nichol
2018年2月28日
Web Scraping in R: rvest Tutorial
Explore web scraping in R with rvest with a real-life project: extract, preprocess and analyze Trustpilot reviews with tidyverse and tidyquant, and much more!
Arvid Kingl
2018年2月27日
Ensemble Learning in R with SuperLearner
Boost your machine learning results and discover ensembles in R with the SuperLearner package: learn about the Random Forest algorithm, bagging, and much more!
Daniel Gremmell
2018年2月20日
Understanding Blockchains by Coding One in R
Implement a small blockchain in R and learn more about what a blockchain looks like and some of the core concepts behind it!
Johannes Mueller
2018年2月8日
Google Cloud for Data Science: Beginner's Guide
Learn to set up a data science environment on Google Cloud: create an instance on Google Compute Engine, install Anaconda and run Jupyter notebooks!
Alexis Perrier
2018年2月6日
Lyric Analysis with NLP & Machine Learning with R
Dive into the lyrics of Prince's music with R: use text mining and Exploratory Data Analysis (EDA) to shed insight on The Artist's career.
Debbie Liske
2018年2月2日
Data Science for Search Engine Marketing (SEM)
In this tutorial, data science meets Search Engine Marketing: learn to create Google AdWords campaigns by generating keywords and ad templates with Python!
Elias Dabbas
2018年1月26日
PEP-8 Tutorial: Code Standards in Python
With this beginner tutorial, you'll start to explore PEP-8, Python's style guide, so that you can start formatting your code correctly to maximize its readability!
Chitrank Dixit
2023年4月11日
Python String Tutorial
In this tutorial, you'll learn all about Python Strings: slicing and striding, manipulating and formatting them with the Formatter class, f-strings, templates and more!
Sejal Jaiswal
2018年1月18日
Time Series Analysis Tutorial with Python
Get Google Trends data of keywords such as 'diet' and 'gym' and see how they vary over time while learning about trends and seasonality in time series data.
Hugo Bowne-Anderson
2018年1月17日
Machine Learning with Kaggle: Feature Engineering
Learn how feature engineering can help you to up your game when building machine learning models in Kaggle: create new columns, transform variables and more!
Hugo Bowne-Anderson
2018年1月10日
8 Useful Shell Commands for Data Science
Which shell commands do data scientists use nearly every day? Discover and learn how to use them in this tutorial!
Alexis Perrier
2018年1月5日