Foundations of Machine Learning

This course is part of Fractal Data Science Professional Certificate

Instructor: Analytics Vidhya

What you'll learn

  •   Construct Machine Learning models using the various steps of a typical Machine Learning Workflow
  •   Apply appropriate metrics for various business problems to assess the performance of Machine Learning models
  •   Develop regression and tree based Machine learning  Models to make predictions on relevant business problems
  •   Analyze  business problems where unsupervised Machine Learning models  could be used to derive value from data
  • Skills you'll gain

  •   Machine Learning
  •   Anomaly Detection
  •   Applied Machine Learning
  •   Exploratory Data Analysis
  •   Data Cleansing
  •   Unsupervised Learning
  •   Decision Tree Learning
  •   Data Processing
  •   Predictive Modeling
  •   Supervised Learning
  •   Regression Analysis
  •   Application Deployment
  •   Statistical Modeling
  •   Machine Learning Algorithms
  •   Data Manipulation
  •   Feature Engineering
  • There are 6 modules in this course

    1. Grasp the fundamental principles of machine learning and its real-world applications. 2. Construct and evaluate machine learning models, transforming raw data into actionable insights. 3. Navigate through diverse datasets, extracting meaningful patterns that drive decision-making. 4. Apply machine learning strategies to varied scenarios, expanding your problem-solving toolkit. This course equips you with the foundation to thrive as a machine learning enthusiast, data-driven professional, or someone ready to explore the dynamic possibilities of machine learning.

    Building Your First Machine Learning (ML) Model for Synergix Solutions

    Evaluating Prediction Models

    Linear and Logistic Regression

    Decision Trees for Synergix Solution

    Introduction to Unsupervised Learning

    Explore more from Data Analysis

    ©2025  ementorhub.com. All rights reserved