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Учебники по Python
Будьте в курсе последних новостей, техник и ресурсов по программированию на Python. В наших учебниках — подробные практические разборы и кейсы, которые помогут вам повысить квалификацию.
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Asyncio: An Introduction
A short introduction to asynchronous I/O with the asyncio package.
8 мая 2017 г.
Scikit-Learn Tutorial: Baseball Analytics Pt 1
A scikit-learn tutorial to predicting MLB wins per season by modeling data to KMeans clustering model and linear regression models.
4 мая 2017 г.
Viewing 3D Volumetric Data With Matplotlib
In this Python tutorial, you'll make use of Matplotlib's event handler API to display the slices of an MRI dataset.
19 апреля 2017 г.
Exploratory Data Analysis of Craft Beers: Data Profiling
In this tutorial, you'll learn about exploratory data analysis (EDA) in Python, and more specifically, data profiling with pandas.
13 апреля 2017 г.
Python Exploratory Data Analysis Tutorial
Learn the basics of Exploratory Data Analysis (EDA) in Python with Pandas, Matplotlib and NumPy, such as sampling, feature engineering, correlation, etc.
15 марта 2017 г.
Python Dictionary Tutorial
In this Python tutorial, you'll learn how to create a dictionary, load data in it, filter, get and sort the values, and perform other dictionary operations.
16 февраля 2017 г.
Scipy Tutorial: Vectors and Arrays (Linear Algebra)
A SciPy tutorial in which you'll learn the basics of linear algebra that you need for machine learning in Python, with a focus how to with NumPy.
8 февраля 2017 г.
Web Scraping and Parsing Data in R | Exploring H-1b Data Pt. 1
Learn how to scrape data from the web, preprocess it and perform a basic exploratory data analysis with R
12 января 2017 г.
Preprocessing in Data Science (Part 3): Scaling Synthesized Data
You can preprocess the heck out of your data but the proof is in the pudding: how well does your model then perform?
10 мая 2016 г.
Preprocessing in Data Science (Part 2): Centering, Scaling and Logistic Regression
Discover whether centering and scaling help your model in a logistic regression setting.
3 мая 2016 г.
Preprocessing in Data Science (Part 1): Centering, Scaling, and KNN
This article will explain the importance of preprocessing in the machine learning pipeline by examining how centering and scaling can improve model performance.
26 апреля 2016 г.