Introduction To Machine Learning For Begineers[Data-Science] 2023

Posted By: ELK1nG

Introduction To Machine Learning For Begineers[Data-Science]
Last updated 7/2023
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz
Language: English | Size: 1.05 GB | Duration: 2h 7m

Learn about Data Science and Machine Learning with Python including Pandas, matplotlib with projects,quizes

What you'll learn

Basics of machine learning on python

Fundamental of machine learning

Learn about different types of machine learning agorithms

Make powerful analysis

Make accurate prediction on different datasets by using machine learning.

Know which Machine learning model to choose for each type of problem

Create complex visualization with matplotlib

Linear regression,Logistic Regression,Knn,Decision Tree,Naive Bayes,Random Forest

Requirements

A working computer with windows OS

Bbasics of python programming

Just some high school mathematics level

Anaconda software

Description

HERE IS WHY UOU SHOULD TAKE THIS COURSE:This course complete guides you to both supervised and unsupervised learning using python.This means ,this course covers all the main aspects of practical Data science and if you take this course you can done with taking other courses or buying books on Python based Data Science.In this age of big data companies across the globe use python to shift through the avalanche of information at their disposal .By becoming proficient in supervised and unsupervised learning in python you can give your company a competitive  edge and boost your careeer to the next level.'''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''LEARN FROM AN EXPERT DATA SCIENTIST WITH 3+ YEARS OF EXPERIENCEMy Name is Aakash Singh and I had also recently Published my Research Paper in INTERNATIONAL JOURNAL IJSR on Machine Learning Dataset.This course will help you to roboust grounding in the main machine learning clustering and classifiation…………………………………………………………………………………………………………………………………………………………………………………………………………NO PRIOR PYTHON OR STATICS OR MACHINE LEARNING KNOWLEDGE IS REQUIRED:You will start by absorbing the most valuable python data science basics and techniques.I use easy to understand hands on methods to simplify and address even the most difficult concepts in python.My course will help you to implement the methods using real data obtained from different sources.after taking this course you will easily use package like Numpy,Pandas and Mathplotlib to work with real data in python.We will go through Lab section on JUPYTER NOTEBOOK terminal ,we will go through lots of real like examples for increasing practical side knowledge of programming and we should not neglect theory section also ,Which is essential for this course for this course by the end of this course you will be able to code in python language and feel confident with Machine Learning and you will be able to create your own program and implement where you want.Most importantly uou will learn to implement these techniques pracitically using python ,you will have access to all the data and scripts used in this course remember i am always around you to support my student. SIGN UP NOW!…… 

Overview

Section 1: Complete machine learning series

Lecture 1 Introduction

Section 2: How Machine Learns?

Lecture 2 how machine learns?

Section 3: Installation of lab

Lecture 3 jupyter notebook installation

Section 4: Introduction To Pandas

Lecture 4 pandas

Section 5: DATA VISUALIZATION

Lecture 5 data visualization

Section 6: DATA PRE-PROCESSING

Lecture 6 Data Preprocessing theory

Lecture 7 Data Preprocessing code

Section 7: LINEAR REGRESSION

Lecture 8 Linear Regression theory

Lecture 9 Linear Regression code

Section 8: LOGISTIC REGRESSION

Lecture 10 Logistic Regression theory

Lecture 11 Logistic Regression code

Section 9: KNN Algorithm

Lecture 12 KNN theory

Lecture 13 KNN code

Section 10: DECISION TREE

Lecture 14 Decision Tree Theory

Lecture 15 Decision Tree code

Section 11: NAIVE BAYES

Lecture 16 Naive Bayes Theory

Lecture 17 Naive Bayes code

Section 12: RANDOM FOREST

Lecture 18 Random Forest Theory

Lecture 19 Random Forest code

Section 13: PROJECT

Lecture 20 Project

Anyone who wants to learn concept of machine learning,Any student in college who want to start career in data science,Any data analysts who want to level up in machine learning