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Machine Learning A-Z: Hands-On Python & R In Data Science

Machine Learning A-Z: Hands-On Python & R In Data Science

Master Machine Learning on Python & R

2 Reviews
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Course Highlights

  • 41 hours on-demand video| 31 articles

  • Full lifetime access | 5 downloadable resources

  • Certificate of Completion

  • SkillsFuture Credit eligible More than 7h of learning time required for the course

Mode of learning: Online self study

Course Overview

Who should do this course ?
  • Anyone interested in Machine Learning.

  • Students who have at least high school knowledge in math and who want to start learning Machine Learning.

  • Any intermediate level people who know the basics of machine learning, including the classical algorithms like linear regression or logistic regression, but who want to learn more about it and explore all the different fields of Machine Learning.

  • Any people who are not that comfortable with coding but who are interested in Machine Learning and want to apply it easily on datasets.

  • Any students in college who want to start a career in Data Science.

  • Any data analysts who want to level up in Machine Learning.

  • Any people who are not satisfied with their job and who want to become a Data Scientist.

  • Any people who want to create added value to their business by using powerful Machine Learning tools

What are the course deliverables ?
  • Master Machine Learning on Python & R

  • Handle specific topics like Reinforcement Learning, NLP and Deep Learning

  • Build an army of powerful Machine Learning models and know how to combine them to solve any problem

  • Handle advanced techniques like Dimensionality Reduction

  • Make robust Machine Learning models

  • Make accurate predictions

  • Know which Machine Learning model to choose for each type of problem

  • Make powerful analysis

  • Create strong added value to your business

More about this course
  • This course has been designed by two professional Data Scientists so that we can share our knowledge and help you learn complex theory, algorithms and coding libraries in a simple way.

  • Part 1 - Data Preprocessing

  • Part 2 - Regression: Simple Linear Regression, Multiple Linear Regression, Polynomial Regression, SVR, Decision Tree Regression, Random Forest Regression

  • Part 3 - Classification: Logistic Regression, K-NN, SVM, Kernel SVM, Naive Bayes, Decision Tree Classification, Random Forest Classification


  • Part 4 - Clustering: K-Means, Hierarchical Clustering

  • Part 5 - Association Rule Learning: Apriori, Eclat

  • Part 6 - Reinforcement Learning: Upper Confidence Bound, Thompson Sampling

  • Part 7 - Natural Language Processing: Bag-of-words model and algorithms for NLP

  • Part 8 - Deep Learning: Artificial Neural Networks, Convolutional Neural Networks

  • Part 9 - Dimensionality Reduction: PCA, LDA, Kernel PCA

  • Part 10 - Model Selection & Boosting: k-fold Cross Validation, Parameter Tuning, Grid Search, XGBoost

I am Interested

Curriculum

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    Reviews

    Average Rating

    4

    Based on 2 Ratings

    Write a Review

    SRIDHARA R

    It was good Course i able to get basics of machine Learning, able to create my own model i able get job by this course

    Kiril ermenko

    Very good for beginners

    This course keeps you engaging and it gives you very good intuition for machine learning.Presentation is good and it takes very good intuition of ml Algorithms. After understanding the Algorithms they carry out programming side by side in Python.They will provide all the instructions in dowlading the required software to carry out the programming part.Two trainers one will explain the Algorithms other will carry out the programming part. There is also some assignments to be finished which they will help us if we don't get. After completion of the course you will get the certification.

    Frequently Asked Questions

    How can I take this course?
    This course is delivered by an instructor through online videos and other documents only. You will be redirected to our partner site for making the payment and then accessing this course. You do not have to go to any classroom in any place for taking this course. You need an internet connection and a computer/laptop/mobile/tablet only.
    Is there a specific time within which I should complete my courses?
    Courses do not expire, and therefore, there is no time frame to complete your courses. Once you purchase this course, you can view it as many times as you want. You can do the course as fast or slow as you want. You can also view it from any machine in the world, whenever you want - forever.
    Do I get a certificate on taking this course?
    On completing the course, you will get a course completion certificate from Udemy.
    Do I get a refund in case I do not like this course?
    We have 7 days exchange policy. Please send email to services@naukri.com in case you have any issues related to the courses you have purchased. We don’t provide any refunds. Please inform about course(s) that you want in exchange of the ones purchased earlier and our support team will help you. This policy will not be applicable if the participant has accessed more than 30% of the e-Learning content or has attended more than 1 class. Applicable only through courses purchased through Naukri Learning. For others, please contact the course provider directly.
    I have some other question. Where can I get help?
    Please send email to e-learning@naukri.com or call our toll-free number 1800-103-4702.
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