by Benjamin Hoff | Released March 2017 | ISBN: 9781785880711

Analyze and understand your data with the power and simplicity of Python About This VideoLearn Data Analysis using modern processing techniques with Numpy, SciPy, and PandasApply Natural Language Algorithms other Machine Learning Algorithms to provide unique and interesting insightsPresent Insights quickly and cleanly through the use of a Dashboard ApplicationIn DetailPython 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. Show and hide more

1. Chapter 1 : Getting Started with Python
   • The Course Overview 00:03:55
   • Getting started with Python 00:26:23
   • Getting Data using the Twitter API 00:20:47
   • Collecting and Storing Tweets 00:09:27
   • Database Design 00:10:31
   • Pandas and Databases 00:05:56
2. Chapter 2 : Numerical Computing with Pandas
   • Panda Series, Dataframes, and Columnar Operations 00:21:21
   • Grouping Operations and Working with Date Columns 00:17:01
   • Merging Operations and Exporting data to JSON/CSV 00:14:54
3. Chapter 3 : Scientific Computing with NumPy/SciPy
   • Array Features, Bucketting Arrays and Histogram Functions 00:21:02
   • Simple Aggregations 00:21:23
   • Linear Algebra 00:04:29
4. Chapter 4 : Presenting stories via simple visualizations
   • Introducting PyQT and MatplotLib 00:31:47
   • Creating Charts 00:07:36
   • Simple XY Plots with Axis Scales 00:04:47
5. Chapter 5 : Using the NLTK Package
   • Introduction to the NTLK Package 00:19:00
   • Bag of Words 00:21:33
   • Classification of Words 00:09:27
   • Stemming 00:11:53
   • Simple Sentiment Analysis 00:05:43
6. Chapter 6 : Getting insights from tweets
   • Grouping By Dimensions and Classification of Data Types 00:25:08
   • Trend Analysis and Deriving New Metrics 00:20:29
   • Correlation Analysis 00:17:28
   • Course Summary 00:03:42
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