در این دوره ی آموزشی با Extension های Jupyter Notebook زبان پایتون آشنا می شوید و استفاده از آن ها را در عمل یاد می گیرید Extension هایی که در این دوره تدریس می گردند برای تیم های Data Science بسیار کاربردی و مفید هستند.

این دوره آموزشی محصول موسسهInfiniteskills است.

سرفصل های این دوره:

  • چگونگی دسترسی به فایل
  • تنظیمات محیط
  • نصب و راه اندازی Jupyter نوت بوک
  • امکانات نوت بوک
  • مرورگر استاندارد
  • برنامه های افزودنی نصب نوت بوک
  • پسوند نوت بوک
  • Conda
  • اسناد Autocreate در HTML و یا PDF
  • به اشتراک گذاری نوت بوک با یک تیم
  • سازماندهی یک گردش کار
  • کنترل نسخه
  • دریافت اطلاعات
  • و ….

عنوان دوره: Infiniteskills Jupyter Notebook for Data Science

مدت دوره: 3 ساعت

نویسنده: Jonathan Whitmore

Infiniteskills Jupyter Notebook for Data Science

Jonathan Whitmore
3 hours

In this project-based Jupyter Notebook for Data Science Teams video tutorial series, you'll quickly have relevant skills for real-world applications.
Follow along with our expert instructor in this training course to get:
Concise, informative and broadcast-quality Jupyter Notebook for Data Science Teams training videos delivered to your desktop
The ability to learn at your own pace with our intuitive, easy-to-use interface
A quick grasp of even the most complex Jupyter Notebook for Data Science Teams subjects because they're broken into simple, easy to follow tutorial videos
Practical working files further enhance the learning process and provide a degree of retention that is unmatched by any other form of Jupyter Notebook for Data Science Teams tutorial, online or offline... so you'll know the exact steps for your own projects.

01. Introduction
Introduction And Course Overview
About The Author
0103 How To Access Your Working Files
02. Setting Up Environment
Installing The Jupyter Notebook And Setup
Setting Up Git And GitHub Account
03. Jupyter Notebook Features
0301 Standard Browser Use
0302 Installing Notebook Extensions
0303 More On Notebook Extensions
0304 SQL Magic And Pandas
0305 Conda Environments
0306 R In Jupyter Notebook
0307 Autocreate Documents In HTML Or PDF
0308 Interactive Widgets
0309 Bleeding Edge - JupyterHub
04. Sharing Notebooks With A Team
0401 Organizing A Workflow
0402 Lab Vs. Deliverable Notebook
0403 Directory Structure And Naming Conventions
0404 Version Control
05. Project - Data Science With The Notebook End-To-End Example
0501 Get Data
0502 Load The Data
0503 Initial Data Cleaning
0504 Creating A New Github Repository
0505 Version Control
0506 Exploratory Data Analysis - Regression Plotting
0507 Exploratory Data Analysis - Variable Transformations
0508 Git Branch Store Data Cleaned Pipeline
0509 Feature Engineering
0510 Random Forest Prediction And Evaluation
0511 Final Analysis Cleanup
0512 Pull Request, Peer Review, And Merge With Master
06. Project - Data Science: Statistics And Data Visualizations
0601 Initial Data Visualization
0602 Advanced Pandas Plotting
0603 Advanced Seaborn Plotting
0604 Statsmodels Analysis - Part 1
0605 Statsmodels Analysis - Part 2
07. Conclusion
0701 Resources And Where To Go From Here