Machine Learning with Python

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Machine Learning with Python

Machine Learning with Python involves using Python, a popular programming language, to implement algorithms and models that enable machines to learn from data and make predictions or decisions. Python's simplicity, flexibility, and extensive libraries make it a leading choice for machine learning (ML) projects.

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Career Growth Prospects

Building a career in machine learning with Python opens up a wide range of opportunities across industries, as Python is one of the most popular languages for machine learning (ML). Mastering Python for ML equips professionals to work on cutting-edge technologies and solve real-world problems using data-driven approaches.

web development job demand High Demand and Growth
The demand for machine learning (ML) with Python is exceptionally high and continues to grow as industries increasingly adopt AI-driven solutions. Python has emerged as the de facto language for ML due to its simplicity, versatility, and extensive library ecosystem, making it a key skill in the job market.

data science career pathaway Career Path and Roles
Machine learning offers a wide range of career roles, Some of the roles include Machine Learning Engineer, Data Scientist, AI Developer, NLP Engineer, Computer Vision Engineer, MLOps Engineer, Business Intelligence Analyst with ML, Research Scientist.

artificial intelligence competitive salaries Competitive Salaries
Machine learning professionals command some of the highest salaries in the tech industry due to their specialized skills, Entry-level roles often offer lucrative packages, and salaries increase significantly with experience and expertise.

opportunity Opportunities for Specialization
Professionals can specialize in areas like: Natural Language Processing (NLP), Computer Vision, Reinforcement Learning, Big Data & Scaleable ML, Edge AI.

Key Takeaways

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Course Curriculum

Introduction to Programming & Programming Language
Introduction to Programming, Introduction to Programming Language, How to Install?, Execution steps, Interactive Shell, User Interface or IDE, Creating Your First Program

Memory Management & Datatypes
Memory Management and Garbage Collection, Object Creation and Deletion, Object Properties, Data Types and Operations, Numbers, String Operations

Data Types
List Tuple, Dictionary, Other Core Types

Statements
Statements and Syntax, Assignments, Expressions and prints, If tests and Syntax Rules, While and For Loops

Operations
File Operations, Opening a file, Using Files, Other File tools, Check If File or Directory Exists, COPY and PASTE File using shutil.copy(), Rename File and Directory using os.rename(), ZIP file with example

Functions
Function Definition and Call, Function Scope, Function Arguments

Modules and Packages
Module Creations and Usage, Types of package, Package creation, Importing packages

Exception Handling
Default Exception Handler, Except Exceptions, Raise an exception, User defined exception

Accessing Internet
Accessing internet data & manipulating XML, using Programming Language.

Important
We will be covering all concepts of programming language using Python.
Classes
Classes and Instances, Classes method calls, Class methods, Instance methods, Static methods

Object Oriented Programming
Abstraction, Encapsulation, Polymorphism, Types of Polymorphism, Inheritance, Types of inheritance

Projects
You will be able to make multiple projects using Python which will help you in understanding vital concepts cleared.
Introduction
Overview of Machine Learning, Starting with Machine Learning, Overview of this training, Terminologies in Machine Learning

Machine Learning
Introduction to Machine Learning, What is Machine Learning?, Types of Machine Learning, How Machine Learning works? Usage of Machine Learning.

Revisiting Python
Introduction to Python Programming, Introduction to Python and Anaconda, Working on Jupyter IDE, Conditional statements in Python, Different types of data, List,Tuple Dictionary, Loops

Function & Packages
Function, Packages, Installing different packages of Python
Python Libraries
Working on Various Python Libraries, NumPy, Pandas, Matplotlib, Scikit-learn

NumPy
Working on NumPy, Introduction to Numpy Array, Creating arrays of different Dimensions, Indexing, Data processing using Array

Pandas
Data Analysis using Pandas, Introduction to Pandas, Data Type of Pandas, Creating Dataframe using Pandas, Importing Dataset using Pandas, Various operations on data using Pandas tools

Matplotlib
Data visualization using Matplotlib, Plotting data using Matplotlib library, Using various tools of Matplotlib, Types of Graph, Implementation of different types of Graphs

Scikit-Learn
Applying Algorithms on Dataset using Scikit-learn, Data splitting, Using different algorithms for dataset, Prediction, Score check
Machine Learning Algorithms
Regression analysis
Simple linear regression
Multi linear regression
Classification
Binary class classification
Multi class classification
Support Vector Machine
KNN algorithm
Datasets
IRIS Dataset
BMI Male Female Dataset
MNIST Dataset
DIGIT Dataset
Titanic Dataset
CIFAR Dataset

Projects
1. Area Price Prediction Project
2. Gender Classification Project
3. Iris Flower Species Classification
4. Digit Recognition Project
5. Survival Prediction on Titanic Project
6. Object Recognition Project
7. Insurance Purchase Prediction Project


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