Problem Solving using PySpark – Regression & Classification

سرفصل های دوره

Gradient Boosted Trees, XGBoost, Spark NLP, Time Series, Prophet, Data Cleaning, Descriptive Statistics, Spark SQL

1. Introduction

1. Introduction.html

2. Problem Solving with PySpark Regression and Classification

2. Data analysis and descriptive statistics with PySpark

1.1 Data for the segment on Descriptive Statistics.html

1.2 metropt+3+dataset.zip

1.3 spark 3 descp stat 1.zip

1. Setting up PySpark Environment in Google Colab

2. Understanding Descriptive Statistics in PySpark

3. Understanding Data Filtering and Slicing in PySpark

4. Summary of Descriptive Statistics in PySpark and Quiz

3. Data Cleaning with PySpark

1.1 Data cleaning.zip

1. Introduction to Data Cleaning with PySpark

2. Setting up PySpark Environment for Data Cleaning on Google Colab

3. Understanding the Dataset Explanatory Analysis and Data Cleaning with PySpark

4. PySpark Data Cleaning Assessment of Null Values and Outliers

5. Data Cleaning with PySpark Imputation Strategy Quiz

6. Introduction to Pivot Tables in PySpark

4. Predictive modeling with PySpark using Regression

1.1 Electric grid.csv

1. Introduction to Regression and Classification Problems in PySpark

2. Understanding the Data Set through Explanatory Analysis

3. Correlation Analysis and Data Preparation

4. Modeling the data using Gradient Boosted Trees Regression

5. Understanding Feature Importance

6. Gradient Boosted Trees Regression - Quiz

5. Predictive Modeling with PySpark using Classification

1.1 Stabf class.csv

1. Classification Problem Statement Supervised Machine Learning

2. Data Cleaning and Preparation for XGBoost Classification Model

3. XGBoost Classification Model Pipeline using PySpark

4. Summary of the segment on Spark XGBoost Classifier

6. Text analytics using PySpark and Spark NLP

1.1 Text data cleaning .zip

1. Classification Model for Text Data

2. Understanding the Data for Text Classification

3. Word Cloud Text Analytics Quiz

4. Spark NLP Pipeline Classification Model

7. Time Series Analysis and Forecast with PySpark and Prophet

1.1 train forecast.zip

1. Introduction to Time Series Analysis Setting up the Google Colab Notebook

2. Explanatory Analysis and Data Cleaning

3. Analysis of time series components using advanced visualization techniques

4. Use of Prophet Model for Time Series Forecasting

5. Time Series Forecasting - Quiz

8. Introduction to Spark SQL

1.1 Spark SQL.zip

1. Introduction to Spark SQL Querying

2. Comparison of PySpark statements and Spark SQL Query

3. Join in Spark SQL

4. Join in Spark SQL - Quiz

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تولید کننده: Udemy