English | MP4 | AVC 1280×720 | AAC 48KHz 2ch | 6 Hours | 1.32 GB
Analyze and understand your data with the power and simplicity of Python
Python features numerous numerical and mathematical toolkits such as: Numpy, Scipy, Scikit learn and SciKit, all used for data analysis and machine learning. With the aid of all of these, Python has become the language of choice for data scientists for data analysis, visualization, and machine learning.
This video aims to teach Python developers how to perform data analysis with the language by taking advantage of the core data science libraries in the Python ecosystem. The learning objective for viewers is to understand how to locate, manipulate, and analyse data with Python, with the ability to analyse large and small sets of data using libraries such as Numpy, pandas, IPython and SciPy.
This is a two part series. The first series is focused on getting and manipulation sizeable amounts of data using modern techniques. The second series is focused on advanced analysis of the data to include modern machine learning techniques.
What You Will Learn
- Advanced and recommend software engineering development practices.
- How to scrape the twitter stream to collect real time data
- Smart storing of data using advanced abstractions and Object-Oriented programming
- Easy and practical data manipulation techniques for dealing with large volumes of data
- Natural Language Processing tools, special designed for working with sentences and other forms of textual data
- Predictive methods that can forecast and predict future trends based on current data
- Data analytics techniques to tease out unseen data relationships
- Dashboard application development to help share and monitor your progress/analysis
Table of Contents
Getting Started with Python
Collecting and Storing Tweets
Getting Data using the Twitter API
Getting started with Python
Pandas and Databases
The Course Overview
Numerical Computing with Pandas
Grouping Operations and Working with Date Columns
Merging Operations and Exporting data to JSON_CSV
Panda Series, Dataframes, and Columnar Operations
Scientific Computing with NumPySciPy
Array Features, Bucketting Arrays and Histogram Functions
Presenting stories via simple visualizations
Introducting PyQT and MatplotLib
Simple XY Plots with Axis Scales
Using the NLTK Package
Bag of Words
Classification of Words
Introduction to the NTLK Package
Simple Sentiment Analysis
Getting insights from tweets
Grouping By Dimensions and Classification of Data Types
Trend Analysis and Deriving New Metrics
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