Stop Being a Beginner in Machine Learning in 2024 | Python

  • Post category:StudyBullet-16
  • Reading time:10 mins read


Master Machine Learning | Data Science using Python only 10 Hours with real-world practices – machine learning projects.

What you will learn

You will be able to build Machine Learning models from scratch

You will have the shortest path to be a Data Scientist

You will be able to answer popular Data Scientist interview questions

You will have complete understanding of all the fundamentals about Machine Learning algorithms

You will master the python libraries for Machine Learning and Data Science

You will easily engage real-world data science and machine learning projects

You will learn all about data preprocessing and visualization

You will learn to use pandas for data analysis

You will learn to use scikit-learn for machine learning

You will learn to use numpy for data manipulation

You will learn regression, classification and clustering machine learning models

You will learn the fundamentals of data science

Description

Welcome to “Stop being a beginner in Machine Learning in 2024 | Python”, a comprehensive and beginner-friendly course designed to fast-track your journey into the world of data science. This course is not just about learning theories; it’s about experiencing data science as it is in the real world, guided by expertise akin to that of a senior data scientist.

Every session in this course is meticulously crafted to reflect the day-to-day challenges and scenarios faced by professionals in the field. You’ll find yourself diving into the core aspects of machine learning, exploring the practical applications of Python in data analysis, and unraveling the mysteries of predictive modeling. Our approach is unique – it combines detailed video tutorials with guided project work, ensuring that every concept you learn is reinforced through practical application.

As you progress through the course, you will develop a solid foundation in Python programming, essential for any aspiring data scientist. We delve deep into data manipulation and visualization, teaching you how to turn raw data into insightful, actionable information. The course also covers critical topics such as statistical analysis, machine learning algorithms, and model evaluation, providing you with a well-rounded skill set.


Get Instant Notification of New Courses on our Telegram channel.


What sets this course apart is its emphasis on real-world application. You will engage in hands-on project work that simulates actual data science tasks. This project-based learning approach not only enhances your understanding of the subject matter but also prepares you for the realities of a data science career.

By the end of this 10-hour journey, you will have not only learned the fundamentals of data science and machine learning but also gained the confidence to apply these skills in real-world situations. This course is your first step towards becoming a proficient data scientist, equipped with the knowledge and skills that are highly sought after in today’s tech-driven world.

Enroll now in “Stop being a beginner in Machine Learning in 2024 | Python” and embark on a learning adventure that will set you on the path to becoming a successful data scientist in 2024 and beyond!

English
language

Content

Introduction

Introduction
Course Structure

What is Data Science, Machine Learning and Data Science Project Process ?

Let’s Begin!
All about Machine Learning.Let’s make first Machine Learning model without code!
Data Science Project Process

Environment Setup

Anaconda Installation – Windows
Anaconda Installation – MacOS

Toolkit Intro: Statistics and python pandas, numpy, matplotlib and seaborn Recap

Download the Notebooks and Other Course Content
Basic Statistics Intro
pandas Intro
numpy Intro
matplotlib and seaborn Intro

Data Preprocessing with Hands-on Python

First Glance to Our Dataset
Reading Data into Python
Detecting Data Leak and Eliminate the Leakage
Null Handling
Encoding
Feature Engineering on Our Geoghraphical Data

Machine Learning Classification Algorithms – All the Logic Behind Them

Logistic Regression Logic
Logistic Regression Key Takeaways
kNN Classifier Logic and Key Takeaways
Decision Tree Classifier Logic
Logistic Regression, kNN and Decision Tree Algorithms Wrap-up
There Are Some Inexpensive Lunches in Machine Learning
Random Forest Classifier Logic – Bagging Algorithm
LightGBM Logic – Boosting Algorithm
XGBoost Logic

General Modelling Concepts

Train Test Split and Overfit-Underfit
More on Overfit-Underfit Concept

Classification Model Evaluation Metrics

Classification Model Evaluation Metrics

Logistic Regression Classifier and kNN Classifier – Hands-on in Python

Data Recap, Separation and Train Test Split
Outlier Elimination
Take a Look at the Test Set Considering Outliers
Feature Scaling
Update the Train Labels After Outlier Elimination
Logistic Regression in Python
kNN Classifier in Python

Decision Tree Classifier and Random Forest Classifier – Hands-on in Python

Decision Tree Classifier in Python
Random Forest Classifier in Python

LightGBM Classifier and XGBoost Classifier – Hands-on in Python

LightGBM Classifier in Python
XGBoost Classifier in Python

Classification Model Selection, Feature Importance and Final Delivery

Classification Model Selection
Feature Importance Concept
LightGBM Classifier Feature Importance
LightGBM Classifier Re-train with Top Features
Final Prediction for Joined Customers

Multi-Class Classification – Hands-on in Python

MultiClass Classification Explanation
MultiClass Classification in Python

Machine Learning Regression Models – Algorithms and Evaluation

Regression Introduction
Linear Regression Logic
kNN, Decision Tree, Random Forest, LGBM and XGBoost Regressors’ Logic
Regression Model Evaluation Metrics

Regression Models in Python – Hands-on Modelling

Linear Regression in Python
LightGBM Regressor in Python

Unsupervised Learning – Clustering Logic and Python Implementation

Unsupervised Learning Logic and Use Cases
K Means Clustering Logic
Evaluation of Clustering
Do the Scaling Before KMeans
KMeans Clustering in Python

You Made It !

Congratz!
Enroll for Free

💠 Follow this Video to Get Free Courses on Every Needed Topics! 💠

Tags: ,