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

  •   Supervised Learning
  •   Feature Engineering
  •   Data Cleansing
  •   Decision Tree Learning
  •   Machine Learning
  •   Statistical Modeling
  •   Applied Machine Learning
  •   Predictive Modeling
  •   Data Manipulation
  •   Application Deployment
  •   Anomaly Detection
  •   Regression Analysis
  •   Exploratory Data Analysis
  •   Unsupervised Learning
  •   Data Processing
  •   Machine Learning Algorithms
  • 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

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