Machine Learning training class for Beginners in Tokyo | Learn Machine Learning | ML Training | Machine Learning bootcamp | Introduction to Machine Learning, Zinnia Mind, 水曜日, 10. 7月 2019

Are you brand new to Machine Learning? Want to see how fun and easy it can be? This Machine  Learning Training class for beginners course offers a step-by-step guide to understanding and working with Machine Learning and Machine Learning algorithms.
Don't worry if you do not know Programming. You can still learn Machine Learning and see how fun it can be to learn and apply Machine Learning in your job or any other applicable scenarios.  Machine Learning uses simple to complex algorithms and has an easy learning curve, and is very forgiving.
Gain a new skill or complete a task by the end of each module, and, by the end of the course, you will be applying Machine Learning to applicable scenarios! You also learn basic principles which can make it easier for you to learn other advanced Machine Learning techniques in the future. 

Course Schedule

Course Duration: 4 weeks (8 sessions)
Tuesdays and thursdays every week
6:00pm - 8:00pm Local time OR US Pacific Daylight Time each day
July 9 - August 1, 2019 US Pacific Daylight time
Check local date and time for 1st session

What are the prerequisites? 

No prerequisite is required.
Even if you do not have programming background you will be able to take this course and learn Machine Learning.

Course Outline

Introduction to Machine Learning
Fundamentals of Machine Learning
Common Use Cases in Machine Learning
Understanding Supervised and Unsupervised Learning Techniques
Similarity Metrics
Distance Measure Types: Euclidean, Cosine Measures
Creating predictive models
Understanding K-Means Clustering
Understanding TF-IDF, Cosine Similarity and their application to Vector Space Model
Implementing Association rule mining
Understanding Process flow of Supervised Learning Techniques
Decision Tree Classifier
How to build Decision trees
Random Forest Classifier
What is Random Forests
Features of Random Forest
Out of Box Error Estimate and Variable Importance
Naive Bayes Classifier
Problem Statement and Analysis
Various approaches to solving a Data Science Problem
Pros and Cons of different approaches and algorithms
Linear Regression
Logistic Regression
Text Mining
Sentimental Analysis

水曜日, 10. 7月 2019, Zinnia Mind, Machine Learning training class for Beginners in Tokyo | Learn Machine Learning | ML Training | Machine Learning bootcamp | Introduction to Machine Learning



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