Ementorhub

Skills you'll gain

Applied Machine Learning

Classification And Regression Tree (CART)

Feature Engineering

Digital Transformation

Business Ethics

Cloud Computing

Artificial Neural Networks

Statistical Machine Learning

Scikit Learn (Machine Learning Library)

Python Programming

Data Quality

Predictive Analytics

Performance Metric

Regression Analysis

Data-Driven Decision-Making

There are 9 modules in this course

What you'll learn: 1. Build Predictive Models Using Python: Gain hands-on experience with Scikit-learn to develop and refine regression and classification models, applying them to real-world scenarios. 2. Diagnose and Improve Model Performance: Identify issues like overfitting and underfitting, apply cross-validation, and select optimal features to ensure robust, generalizable results. 3. Leverage Advanced Techniques: Explore neural networks, regularization, and cloud-based tools to scale and optimize predictive analytics for complex business challenges. 4. Integrate Analytics into Decision-Making: Translate data-driven insights into actionable strategies to drive innovation and efficiency in digital transformation initiatives.

Introduction to Predictive Analytics

Our First Model

Adding Complexity

Predictive Analytics in Python

Training Advanced Models

Putting it All Together

Neural Networks in Python

Practicum