Ementorhub

What you'll learn

The concept of various machine learning algorithms.

How to apply machine learning models on datasets with Python in Jupyter Notebook.

How to evaluate machine learning models.

How to optimize machine learning models.

Skills you'll gain

Unsupervised Learning

Python Programming

Performance Metric

Time Series Analysis and Forecasting

Natural Language Processing

Machine Learning Algorithms

Text Mining

Pandas (Python Package)

Feature Engineering

Applied Machine Learning

Scikit Learn (Machine Learning Library)

Predictive Modeling

Machine Learning

Jupyter

Data Processing

Statistical Analysis

Supervised Learning

Regression Analysis

There are 9 modules in this course

Accounting Data Analytics with Python is a prerequisite for this course. This course is running on the same platform (Jupyter Notebook) as that of the prerequisite course. While Accounting Data Analytics with Python covers data understanding and data preparation in the data analytics process, this course covers the next two steps in the process, modeling and model evaluation. Upon completion of the two courses, students should be able to complete an entire data analytics process with Python.

Module 1: Introduction to Machine Learning

Module 2: Fundamental Algorithms I

Module 3: Fundamental Algorithms II

Module 4: Model Evaluation

Module 5: Model Optimization

Module 6: Introduction to Text Analysis

Module 7: Introduction to Clustering

Module 8: Introduction to Time Series Data