Pandas for Predictive Analysis using scikit-learn

Pandas for Predictive Analysis using scikit-learn

English | MP4 | AVC 1920×1080 | AAC 44KHz 2ch | 1h 12m | 334 MB

Master top rated Python library, Pandas for real-world data analysis. Learn how to use Pandas for Predictive Analysis by employing scikit-learn

In this course we learn that stand alone data analysis is fine but what most companies these days are looking for is to do Predictive analysis using their data. In this advanced course, we will make you ready to start doing Predictive Analysis on your data by showing you how to build Machine Learning models with scikit-learn and pandas.

In this course, you will be training models and be making data based predictions using scikit-learn.The user will like this as a standalone product as Making Predictions data using Machine Learning is an absolute minimum skill for any Data Analyst Data Scientist these days. We will teach users how to use scikit-learn to make data based predictions. User will learn how to bring in their data using pandas, apply some machine learning models and take out the predictions. We will also walk the user through various popular Machine Learning algorithms.

By the end of this course, the user will be quite confident of doing Predictive Analysis on their own. This subject matter is big enough that 2-3 hours of stand alone course is absolute bare minimum to achieve it.

What You Will Learn

  • Learn to read different kinds of data into Pandas Dataframes for data analysis.
  • Discover how to manipulate, transform and apply formulas on the data imported into the pandas dataframes
  • See how to analyze and visualize different kinds of data using Pandas, to gain real world insights.
  • Get to know how to use Pandas to make predictions using Machine Learning and scikit-learn
  • Work with Big Data using Pandas, and get useful information for your business decisions
  • Practice data analysis with quantitative financial data and see how to model time-series data, perform algorithmic trading
  • Take your Pandas to the next level by learning advanced techniques.
  • Get to know how to take out transformed data out of Pandas dataframes and into the formats your application expects.
Table of Contents

01 The Course Overview
02 Setting Up scikit-learn for Machine Learning
03 Preprocessing Your Data to Make It Ready for Training a Model
04 Training and Running the Classification Model
05 Getting Your Own Data Ready for Machine Learning
06 Evaluating a Machine Learning Model
07 Selecting Best Features for Training the Model
08 Tuning Feature Performance
09 Using Naive Bayes Classification Algorithm
10 Building Models Using Support Vector Machine
11 Using Decision Tree Classifiers
12 Making Your Bag of Words Ready
13 Building and Training a Model
14 Making Predictions