This is the bite size course to learn Python Programming for Machine Learning and Statistical Learning. In CRISP DM data mining process, machine learning is at the modeling and evaluation stage.
You will need to know some Python programming, and you can learn Pythonprogramming from my "Create Your Calculator: Learn Python Programming Basics Fast" course. You will learn Python Programming for machine learning and you will be able to train your own prediction models with naive bayes, decision tree, knn, neural network, linear regression, and evaluate your models very soon after learning the course.
I have created Applied statistics using Python for data understanding stage and advanced data visualizations for data understanding stage and includes some data processing for data preparation stage.
You can look into the following courses to get SVBook Certified Data Miner using Python
SVBook Certified Data Miner using Python are given to people who have completed the following courses:
- Create Your Calculator: Learn Python Programming Basics Fast (Python Basics)
- Applied Statistics using Python with Data Processing (Data Understanding and Data Preparation)
- Advanced Data Visualizations using Python with Data Processing (Data Understanding and Data Preparation)
- Machine Learning with Python (Modeling and Evaluation)
and passed a 50 questions Exam. The four courses are created to help learner understand about Python programming basics, then applied statistics (descriptive, inferential, regression analysis) and data visualizations (bar chart, pie chart, boxplot, scatterplot matrix, advanced visualizations with seaborn, and Plotly interactive charts ) with data processing basics to understand more about the the data understanding and data preparation stage of IBM CRISP DM model. Learner will then learn about machine learning and confusion matrix, which is the modeling and evaluation stages of the IBM CRISP DM model. Learner will be able to do data mining project after learning the courses.
Content
Getting Started
Getting Started 2
Getting Started 3
Getting Started 4
Data Mining Process
Download Data set
Read Data set
Simple Linear Regression
Build Linear Regression Modela: Train and Test set
Build and Predict Linear Regression Models
KMeans Clustering
KMeans Clustering in Python
Agglomeration Clustering
Agglomeration Clustering in Python
Decision Tree ID3 ALgorithm
Decision Tree in Python
KNNClassification
KNN in Python
Naive Bayes Classification
Naive Bayes in Python
Neural Network Classification
Neural Network in Python
What Algorithm to Use?
Model Evaluation
Model Evaluation using Python for Classification
Model Evaluation using Python for Regression
