Description
In this section, we’ll delve into the fundamentals of predictive modeling with machine learning, focusing specifically on techniques implemented in Python.
We’ll explore various aspects of building predictive models, from data preprocessing to model evaluation, leveraging the powerful libraries available in the Python ecosystem.
Through practical examples and step-by-step guidance, you’ll gain a solid understanding of how to apply machine learning algorithms to real-world datasets for predictive analysis. Let’s embark on this journey into the realm of predictive modeling with Python!
TABLE OF CONTENT
1 . Introduction to Predictive Modeling
Overview of Predictive Modeling
Importance and Applications
Fundamentals of Machine Learning
Python Setup and Environment
2 . Data Preprocessing
Data Cleaning
Handling Missing Values
Feature Scaling
Handling Categorical Data
Data Transformation and Encoding
3 . Exploratory Data Analysis (EDA)
Descriptive Statistics
Data Visualization in Machine Learning using Python
Correlation Analysis
Feature Importance
5 . Supervised Learning Algorithms
Linear Regression
Decision Trees
Random Forest
Support Vector Machines
k-Nearest Neighbors
Gradient Boosting
6 . Model Evaluation and Validation
Training and Testing Data Split
Cross-Validation
Performance Metrics (e.g., accuracy, precision, recall, F1-score)
ROC-AUC Curve
7 . Hyperparameter Tuning
Grid Search in Machine Learning using Python
Random Search
Optimizing Model Parameters
8 . Feature Selection and Engineering
Importance of Feature Selection
Feature Importance Techniques
Creating New Features
9 . Unsupervised Learning
Clustering (e.g., K-Means, Hierarchical)
Dimensionality Reduction (e.g., PCA)
10 . Time Series Forecasting
Introduction to Time Series Data
ARIMA Models in Machine Learning using Python
Seasonal Decomposition
Forecasting Techniques
11 . Model Deployment
Saving and Loading Models
Web-based Model Deployment
Model Monitoring and Maintenance
Please Visit python Official Site: || Locus Academy has more than a decade experience in delivering the training/staffing onĀ Predictive Modeling with Machine Learning using Python for corporates across the globe. The participants for the training/staffing on Predictive ModelingĀ are extremely satisfied and are able to implement in their on going projects.
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