Practical Data Analysis and Visualization with Python

Practical Data Analysis and Visualization with Python, available at $19.99, has an average rating of 4, with 42 lectures, based on 55 reviews, and has 301 subscribers.

You will learn about Understand the logic behind machine learning models without strain Build forecasting models with machine learning Analyze customer satisfaction Analyze bank statements Classify images Learn how to preprocess data Develop classification models Build Fraud Detection models Logistic Regression models k-nearest neighbor models Random Forest Models Support Vector Machines Learn NumPy package Learn Pandas package Learn Scikit-learn Filter and Slice datasets Visualize data with Matplotlib Visualize data with Seaborn Get comfortable creating Pie charts, Donut charts, Bar charts, Line charts, Scatter plots and more Read data from Google Sheets Splitting data into training and test sets Classify objects with Naive Bayes Develop supervised learning models Linear Regression models This course is ideal for individuals who are Anyone who wants to learn data analysis and visualization or Anyone how has a will and / or a need for data analysis or Anyone who wants to build machine learning models to solve day-to-day problems It is particularly useful for Anyone who wants to learn data analysis and visualization or Anyone how has a will and / or a need for data analysis or Anyone who wants to build machine learning models to solve day-to-day problems.

Enroll now: Practical Data Analysis and Visualization with Python

Summary

Title: Practical Data Analysis and Visualization with Python

Price: $19.99

Average Rating: 4

Number of Lectures: 42

Number of Published Lectures: 42

Number of Curriculum Items: 42

Number of Published Curriculum Objects: 42

Original Price: $89.99

Quality Status: approved

Status: Live

What You Will Learn

• Understand the logic behind machine learning models without strain
• Build forecasting models with machine learning
• Analyze customer satisfaction
• Analyze bank statements
• Classify images
• Learn how to preprocess data
• Develop classification models
• Build Fraud Detection models
• Logistic Regression models
• k-nearest neighbor models
• Random Forest Models
• Support Vector Machines
• Learn NumPy package
• Learn Pandas package
• Learn Scikit-learn
• Filter and Slice datasets
• Visualize data with Matplotlib
• Visualize data with Seaborn
• Get comfortable creating Pie charts, Donut charts, Bar charts, Line charts, Scatter plots and more
• Read data from Google Sheets
• Splitting data into training and test sets
• Classify objects with Naive Bayes
• Develop supervised learning models
• Linear Regression models

Who Should Attend

• Anyone who wants to learn data analysis and visualization
• Anyone how has a will and / or a need for data analysis
• Anyone who wants to build machine learning models to solve day-to-day problems

Target Audiences

• Anyone who wants to learn data analysis and visualization
• Anyone how has a will and / or a need for data analysis
• Anyone who wants to build machine learning models to solve day-to-day problems