Overview

Machine Learning – Classification and Forecasting

Machine learning is a powerful tool for classification and forecasting tasks, which are at the core of data-driven decision-making. This two day course, designed for beginners, provides a comprehensive introduction to classification and forecasting using machine learning algorithms. Participants will learn the fundamentals, practical application, and best practices in predictive modeling.

Skills Covered

By the end of this course, participants will:

  • Understand the concepts of classification and forecasting and their relevance in machine learning.
  • Be proficient in applying classification algorithms to categorize data.
  • Gain practical experience in building and evaluating classification models.
  • Learn the techniques for time series forecasting.
  • Develop the skills to apply predictive modeling to real-world problems.
  • Feel confident to continue exploring more advanced machine learning techniques

Prerequisites

There are no prerequisites required to attend this course.

Target Audience

  • Beginner level courses for aspiring Data Scientist.
  • Anyone who is interested in data science.

Course Curriculum

Module 1: Classification in Machine Learning

  • Introduction to classification and its importance.
  • Supervised vs. unsupervised classification.
  • Data preprocessing for classification tasks.
  • Classification algorithms: Logistic Regression, Decision Trees, and Random Forest.
  • Model evaluation and metrics: Accuracy, Precision, Recall, F1-Score.
  • Practical exercises and projects with classification.

Module 2: Time Series Forecasting and Beyond

  • Introduction to time series data and forecasting.
  • Time series data preprocessing and feature engineering.
  • Time series forecasting algorithms: ARIMA and Exponential Smoothing.
  • Beyond time series: Forecasting with machine learning.
  • Model evaluation for forecasting tasks.
  • Hands-on projects and application of classification and forecasting.

Dates & Locations

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Exam & Certification

This course is not associated with any Certification.

Training & Certification Guide

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