Search Results for “Machine Learning”

  1. Machine Learning Using Python

    Description: Machine Learning Certification Training using Python helps you gain experienced professionalsise in various machine learning algorithms such as regression, clustering, decision trees, random forest, NaΓ―ve Bayes and Q-Learning. This Machine Learning using Python Training exposes you to concepts of Statistics, Time Series and different classes of machine learning algorithms like supervised, unsupervised and reinforcement algorithms. Throughout the Data Science Certification Course, you’ll be solving real-life case studies on Media, Healthcare, Social Media, Aviation, HR.
    Platform: Edureka
    Course Level: Newbie
    Duration: 2 Months
    Domain: Artificial Intelligence
    Paid/Free: Paid

  2. Machine Learning with Mahout Certification Training

    Description: An online course designed to provide a blend of Machine learning & Big Data and where Mahout fits in the Hadoop Ecosystem.
    Platform: Edureka
    Course Level: Newbie
    Duration: 2 Months
    Domain: Artificial Intelligence
    Paid/Free: Paid

  3. Intro to Machine Learning with Tensorflow

    Description: Learn foundational machine learning techniques – from data manipulation to unsupervised and supervised algorithms.
    Learning Outcome: Supervised Learning, Deep Learning, Unsupervised Learning
    Platform: Udacity
    Course Level: Newbie
    Duration: 3 Months
    Domain: Artificial Intelligence
    Paid/Free: Paid

  4. Intro to Machine Learning with PyTorch

    Description: Learn foundational machine learning techniques – from data manipulation to unsupervised and supervised algorithms.
    Learning Outcome: Supervised Learning, Deep Learning, Unsupervised Learning
    Platform: Udacity
    Course Level: Newbie
    Duration: 3 Months
    Domain: Artificial Intelligence
    Paid/Free: Paid

  5. Machine Learning Engineer

    Description: Learn advanced machine learning techniques and algorithms – including how to package and deploy your models to a production environment.
    Learning Outcome: Software Engineering Fundamentals, Machine Learning in Production, Machine Learning Case Studies, Machine Learning Capstone
    Platform: Udacity
    Course Level: Expert
    Duration: 3 Months
    Domain: Artificial Intelligence
    Paid/Free: Paid

  6. Machine Learning for Business

    Description: This course will introduce the key elements of machine learning to the business leaders. We will focus on the key insights and base practices how to structure business questions as modeling projects with the machine learning teams. You will understand the different types of models, what kind of business questions they help answer, or what kind of opportunities they can uncover, also learn to identify situations where machine learning should NOT be applied, which is equally important. You will understand the difference between inference and prediction, predicting probability and amounts, and how using unsupervised learning can help build meaningful customer segmentation strategy.
    Learning Outcome: Machine learning and data use cases, Machine learning types, Business requirements and model design, Managing machine learning projects
    Platform: Datacamp
    Course Level: Newbie
    Duration: 4 hours
    Domain: Machine Learning
    Paid/Free: Paid

  7. Machine Learning for Everyone

    Description: In this non-technical course, you’ll learn everything you’ve been too afraid to ask about machine learning. There’s no coding required. Hands-on exercises will help you get past the jargon and learn how this exciting technology powers everything from self-driving cars to your personal Amazon shopping suggestions. How does machine learning work, when can you use it, and what is the difference between AI and machine learning? They’re all covered. Gain skills in this hugely in-demand and influential field, and discover why machine learning is for everyone!
    Learning Outcome: What is Machine Learning?, Machine Learning Models, Deep Learning
    Platform: Datacamp
    Course Level: Newbie
    Duration: 4 hours
    Domain: Machine Learning
    Paid/Free: Paid

  8. Practicing Machine Learning Interview Questions in R

    Description: In this course, you will learn to answer 30 non-trivial questions that often pop up in ML interviews. These questions revolve around seven important topics: data preprocessing, data visualization, supervised learning, unsupervised learning, model ensembling, selection, and evaluation. You will practice these concepts while learning to predict the rating of an Android app or segmenting mall customers based on their purchasing behaviors.
    Learning Outcome: Data preprocessing and visualization, Supervised learning, Unsupervised learning, Model selection and evaluation
    Platform: Datacamp
    Course Level: Newbie
    Duration: 4 hours
    Domain: Machine Learning
    Paid/Free: Paid

  9. Machine Learning in the Tidyverse

    Description: This course will teach you to leverage the tools in the “tidyverse” to generate, explore, and evaluate machine learning models. Using a combination of tidyr and purrr packages, you will build a foundation for how to work with complex model objects in a “tidy” way. You will also learn how to leverage the broom package to explore your resulting models. You will then be introduced to the tools in the test-train-validate workflow, which will empower you evaluate the performance of both classification and regression models as well as provide the necessary information to optimize model performance via hyperparameter tuning.
    Learning Outcome: Foundations of “tidy” Machine learning, Multiple Models with broom, Build, Tune & Evaluate Regression Models, Build, Tune & Evaluate Classification Models
    Platform: Datacamp
    Course Level: Newbie
    Duration: 4 hours
    Domain: Machine Learning
    Paid/Free: Paid

  10. Machine Learning for Marketing Analytics in R

    Description: This is your chance to dive into the worlds of marketing and business analytics using R. Day by day, there are a multitude of decisions that companies have to face. With the help of statistical models, you’re going to be able to support the business decision-making process based on data, not your gut feeling. Let us show you what a great impact statistical modeling can have on the performance of businesses. You’re going to learn about and apply strategies to communicate your results and help them make a difference.
    Learning Outcome: Modeling Customer Lifetime Value with Linear Regression, Logistic Regression for Churn Prevention, Modeling Time to Reorder with Survival Analysis, Reducing Dimensionality with Principal Component Analysis
    Platform: Datacamp
    Course Level: Newbie
    Duration: 4 hours
    Domain: Machine Learning
    Paid/Free: Paid