 BEST DATA SCIENCE, ML, AI, DIGITAL MARKETING COURSE IN KOLKATA

## The Best Machine Learning Training Course in Kolkata

• 80 hours of intensive training
• Taught by SMEs from the industry
• 2 Live Projects
• More than 60 assignments
• Guidance even after training
• LMS access for life

## Machine Learning Course in Kolkata Overview

Machine Learning (ML) is an important part of Artificial Intelligence (AI).

Unlike coding various programs explicitly, Machine Learning provides the computers the ability to learn on its own. How does this work? Numerous algorithms and statistical models are used by the computer which helps it to find hidden patterns in the data provided. These patterns help the computer take an accurate guess as to what the outcome will be for new, unknown data. The best part about any ML algorithm is that its ability to predict the outcome increases and the accuracy improves over time when new data is provided.

#### Skills in machine learning are in great demand.Our industry-relevant Machine Learning course will help you be industry-ready in this new technology. Take advantage of the immense opportunities it presents to advance your career in this emerging field.

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## Things You Will Learn in The Best Machine Learning Training Course in Kolkata

Demo

• Data Types
• Random Variable
• Probability
• Probability Distribution
• Sampling Funnel
• Measure Of central tendency
• Measures of Dispersion
• Expected Value
• Graphical Techniques
• Introduction to R
• R Studio
• Introduction to Python (Installation basic commands)
• Python & R Contd…Skewness & Kurtosis
• Box Plot
• Normal Distribution
• Sampling Variation
• CLT
• Confidence interval
• Intro to HT, 2 sample t test, 1 sample tests
• Other parametric and non parametric test
• By R Code
• Scatter Diagram
• Corr Analysis
• Principles of Regression
• Intro to Simple Linear Regression
• Multiple Linear Regression
• Principles of Logistic regression
• Multiple Logistic Regression
• ROC curve
• Gain chart
• Binomial
• Neg Binomial
• Poission
• Poission
• Neg Binomial
• Models with Excessive ‘0’s
• Multinomial Regression
• Naïve Bayes
• Decision Tree & Random Forest
• Bagging and boosting
• ANN & SVM

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