Data Science/MachineLearning Project Deployment Mastery

Udemy

Online

₹ 385 2240

Quick Facts

particular	details
Medium of instructions English	Mode of learning Self study	Mode of Delivery Video and Text Based

Course and certificate fees

Fees information

₹ 385 ₹2,240

certificate availability

Yes

certificate providing authority

Udemy

The syllabus

Course Overview

Course Curriculum

Introduction To Jupyter Notebook

Jupyter Notebook: Getting Started With Anaconda
Jupyter Notebook: Code Vs Markdown Vs Raw
Jupyter Notebook: Working With Text
Jupyter Notebook: Working With Code(Saving & Exporting Notebook)

Introduction To Google Colab

Google Colab: Overview
Google Colab: Working With Text
Google Colab: Saving & Exporting Notebook
Guide To Setup Jupyter Notebook(Anaconda) and Google Colab
Loading Dataset In Colab

Python For Data Science And Machine Learning

Lecture Resources
Introduction to Python
Data Types In Python
List In Python
Operations On Python List-Split,Count,Index, Reverse,Append,Remove,Pop,Sort,Copy
Range in Python
List Comprehension In Python
Dataframe In Python
SET In Python
Dictionary In Python
Functions In Python
Conditional Statements In Python

Numpy

Introduction To Numpy
Operations On Numpy
Indexing And Slicing 1
Indexing And Slicing 2
Numpy Assignment

Pandas

Pandas Dataframe 1: Series
Iloc and Loc For Pandas Dataframe
Pandas Dataframe
Operations On Pandas Dataframe: Slicing Columns, Adding/Drop Columns and Rows
Operations On Pandas DataFrame: Setting Column Index, Rename DataFrame Columns
Reading Dataset In Pamdas
Working With Dataset: Checking for Missing/Null Values, Head of dataset,Describe
Working With Dataset: Fillna, Sorting,Value_Counts,Concatenation,Join&Merge
Join And Merge In Pandas
Pandas Exercise

Data Visualisation: MatplotIib And Seaborn

Data Visualisation: Matplotlib and Seaborn
Data Visualisation 2
Data Visualisation 3
Univariate Data Analysis
Bivariate And Multivariate Data Analysis
Data Visualisation Assignment

Python Assignment

Python Assignment

Statistics For Data Science And Machine Learning

Lecture Resources
Overview
Statistical Methods
Data Types
Data Sources | Common Statistical Terms
Frequency Distribution
Central Tendency (Mean, Median, Mode)
Measure Of Dispersion
The Five(5) Number Summary
Correlation
Probability
Baye's Theorem
Normal Distribution-Empirical Rule | Central Limit Theorem | Skewness
Hypothesis Testing
Statistics Exercise

Machine Learning

Lecture Resources
Introduction
Applications Of Machine Learning

Supervised Machine Learning

Supervised Machine Learning
Difference Between Regression And Correlation

Linear Regression

Linear Regression
Lab Session 1: Exploratory Data Analysis(EDA)
Lab Session 2: EDA| Dealing With Categorical And Missing Values
Lab Session 3: Building Linear Regression Model
Linear Regression Assignment

Logistic Regression

Introduction 1
Introduction 2
Lab Session 1: Exploratory Data Analysis(EDA)
Lab Session 2: Exploratory Data Analysis(EDA)
Lab Session 3: Building Logistic Regression Model
Logistic Regression Assignment

Naive Bayes Classifier

Introduction
Lab Session

K-Nearest Neighbor (KNN)

Introduction
KNN Distance Measures
Lab Session
Lab Session: Building KNN Model
Choosing K In K-NN
KNN Assignment

Support Vector Machine (SVM)

Introduction
Dealing With Linearly Inseparable Points
Lab Session 1: Exploratory Data Analysis(EDA)
Lab Session 2: Building A Support Vector Machine (SVM) Model

Unsupervised Machine Learning: Clustering

Difference Between KNN and K-Means Algorithms

K-Means Clustering

What Is K-Means Clustering?
Lab Session 1: Exploratory Data Analysis(EDA)
Choosing K in K-Means-The Elbow Method

Hierarchical Clustering

Introduction
Dendrograms And Cophenetic correlation
Lab Session

Unsupervised Learning Project

Assignments for Unsupervised Machine learning

Hands-On Project

Introduction

Breast Cancer Detection Using SVM And KNN

Lecture Resources
Introduction
Summary Of Dataset
Data Preprocessing
Exploratory Data Analysis (EDA)
Model Building

Bank Note Analysis

Introduction
Lecture Resources
Bank Note Analysis-EDA
Bank Note Analysis-Getting Our Dataset Ready For Model Building
Model Building 1
Model Building 2
Model Building 3

Predicting Compressive Strength of Concrete-(Compare performance of 18 models)

Lecture Resources
Introduction
Data Preprocessing
Exploratory Data Analysis (EDA) 1
Exploratory Data Analysis (EDA) 2
Feature Engineering
Model Building 1
Model Building 2

Credit Card Fraud Detection-(Dealing With Data Imbalance)

Introduction
Exploratory Data Analysis (EDA)
Model Building 1
Model Building 2

Stock Market Clustering Using K-Means Algorithm

Lecture Resources
Introduction
Data Extraction And Analysis
Model Building

BigMart Sales Prediction

Lecture Resources
Introduction
Exploratory Data Analysis (EDA)
Feature Engineering, Selection And Transformation
Model Building

Amazon Employee Access Challenge

Lecture Resources
Introduction
Exploratory Data Analysis (EDA)
Model Building 1
Model Building 2

Project Assignment

Based on the given data, will a customer subscribe to a term deposit or not?

Streamlit Project

Lecture Resources
Streamlit Demo
Introduction to Streamlit 1
Introduction to Streamlit 2
Introduction to Streamlit 3
Building Your First Streamlit App
Building Your First Streamlit App-Advance 1
Building Your First Streamlit App-Advance 2
Building Your First Streamlit App-Advance 3
Project Assignment

Flask Tutorial

Introduction To Flask
Create Your First Flask App
Create Your First Flask App: Linking HTML File
Create Your First Flask App: Linking CSS File

Flask PROJECT and DEPLOYMENT

Lecture Resources
Flask Introduction
Introduction to Dataset
Exploratory Data Analysis (EDA)
Model Building
Hands-On With Flask
Creating The Necessary Folders
Creating Folder Contents
Final Deployment
Project Assignment

Heroku Deployment

Lecture Resources
Heroku Introduction
Exploratory Data Analysis (EDA)
Feature Engineering
Further Data Preparation
Model Building And Hyperparameter Tuning
Heroku Deployment 1
Heroku Deployment 2
Project Assignment

Google Cloud Deployment

Lecture Resources
Google Cloud Introduction
GCP Deployment Lesson
Project Assignment

Amazon Web Service(AWS) Deployment

Lecture Resources
AWS Introduction
Dataset
App.py File
PART 1
PART 2
Project Assignment

Microsoft Azure Deployment

Lecture Resources
Azure Deployment
Project Assignment

Final Project

Introduction
Final Machine Learning Project

Instructors

Mr Briit
Instructor
Udemy

Articles

Latest Articles

Data Science vs Data Analytics vs Machine Learning Updated On 06 Feb, 2024

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