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Machine Learning

Data Science Tutorial

Welcome to the world of Data Science. Here, we uncover hidden insights in data to guide smarter choices. Learn Data Science to open doors to endless opportunities. In today's data-driven era, turning information into valuable insights is a game-changer.

AlmaBetter’s Data Science Tutorial for Beginners is an introductory course that provides an overview of the field of data science which includes modules such as Machine Learning, Supervised Learning, Unsupervised Learning, MLOPS, Regression and many more deep concepts of data science.

AlamBetter Tutorials are the best platform to learn data science from scratch. Our free Data Science Tutorial is the best way to learn data science online as it provides you the freedom to learn at your own pace and enjoy the learning to the fullest.

Modules Explored in Our Data Science Tutorial:

Getting Started with Machine Learning
Data preparation and EDA
Supervised Learning
Regression
Classification
Non-Linear Model
Unsupervised Learning
MLOPS

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Module 1

Getting Started with Machine Learning

Introduction to Machine Learning

Types of Machine Learning Model

Applications of Machine Learning

Module 2

Data preparation and EDA

Data Cleaning in Data Science

Data Normalization in Machine Learning

Introduction to Exploratory Data Analysis (EDA)

Feature Engineering for Machine Learning

Module 3

Supervised Learning

Introduction to Supervised Learning

Regression in Machine Learning

Classification in Data Science

Module 4

Regression

Linear Regression in Machine learning

Understanding Bias Variance Tradeoff

Regularization in Machine Learning

Metrics to Measure Regression Models

Module 5

Classification

Logistic Regression in Machine Learning

Decision Trees in Machine Learning

Ensembles of Decision Trees

Random Forest Algorithm in Machine Learning

AdaBoost Algorithm in Machine Learning

Gradient Boosting Algorithm for Machine Learning

XGBoost Algorithm in Machine Learning

Metrics for Classification Model

Module 6

Non-Linear Model

K-Nearest Neighbors(KNN)

Support Vector Machines (SVMs)

Naive Bayes Classifier

Module 7

Unsupervised Learning

What is Unsupervised Learning?

K-means Clustering

Hierarchical Clustering in Machine Learning

Metrics for Unsupervised Learning

Module 8

MLOPS

What is MLOPS?

Stakeholders and Terminologies Used in MLOPS

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