Machine Learning (ML)
Machine learning is a combination of Data Analysis, predictions and algorithms based on which a machine can learn to react on particular data
Machine Learning
Machine learning is a branch of artificial intelligence that focuses on developing algorithms and models that allow computers to learn and make predictions or decisions based on patterns and data, without being explicitly programmed.
This Tech Cryptor’s Machine Learning course dives deep into the fascinating world of machine learning. Through hands-on projects, real-world examples, and expert guidance, you’ll gain a solid foundation in data preprocessing, model training, evaluation, and deployment. Join this transformative journey and unlock the power to extract valuable insights, make accurate predictions, and drive innovation through the incredible capabilities of machine learning.
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What is Machine Learning ?
Introduction and overview about machine learning
Explanation about different types of machine learning with different application and algorithm examples
Introduction to different machine learning terminologies
Installing and Understanding R Studio Software, and Learning syntax of it.
Coding practically for understanding loops, data types, operators etc.
Coding for different Regression algorithms in R Language.
Prediction using different Regression Algorithms.
Coding for different Classification algorithms in R Language.
Prediction using different classification Algorithms.
Installation of software like python for machine learning
Learn about various Data Types used in Python practically.
Learn about rules of Variables, Input/Output in Python.
Learn and code about Arithmetic, Relational, Logical, Assignment, etc. Operators used in Python.
Create and understand different types loops, switch statements.
Performing and understanding data types, strings etc. practically.
Learn about simple linear regression for modelling the relationship between a scalar response and one or more explanatory variables
Learn about multi-linear regression for predicting the value of one dependent variable based on two or more independent variables
Learn logistic regression which predicts the output of a categorical dependent variable
Learn polynomial regression that models the relationship between a dependent and independent variable as nth degree polynomial
Learn decision tree classification which makes predictions based on how a previous set of questions were answered
Learn about random forest classification algorithm which consisting of many decisions trees
Learn about support vector machine classification to create the best line or decision boundary that can segregate n-dimensional space into classes
Learn about K-nearest neighbour algorithm which stores all the available data and classifies a new data point based on the similarity
Learn bagging algorithm which reduces variance within a noisy dataset
Coding for different Regression algorithms in Python.
Coding for different Classification algorithms in Python.
Practically understanding logic behind image extraction.
Coding for making DIGIT RECOGNITION project by Importing packages.
Performing digit recognizer practically on your laptop.
Practically performing them to get output by understanding logic.
Making code for extracting images into our system and reading them.
Making your own project for Converting Images into Texts.
Understanding basic logic behind Graphical User Interface using Python.
Creating own TIC-TAC-TOE game using GUI features.
Coding for making TIC-TAC-TOE as AUTO PLAYER game.
Coding for controlling system using voice commands.
Coding for performing different operations using voice commands.
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