Friday, November 5, 2021

Home Free Course Machine Learning in Python with 5 Machine Learning Projects Free Video Course

Machine Learning in Python with 5 Machine Learning Projects Free Video Course

November 05, 2021 Free Course,

Course Video Size : 18 GB High Quality Video Content

part 01

part 02

part 03

part 04

part 05

part 06

part 07

part 08

part 09

Original Author: Click Here

Learn Complete Machine Learning Bootcamp with Python. Build 5 Complete Machine Learning Real World Projects with Python.

What you will learn from this Course:

Theory and practical implementation of linear regression using sklearn
Theory and practical implementation of logistic regression using sklearn
Feature selection using RFECV
Data transformation with linear and logistic regression.
Evaluation metrics to analyze the performance of models
Industry relevance of linear and logistic regression
Mathematics behind KNN, SVM and Naive Bayes algorithms
Implementation of KNN, SVM and Naive Bayes using sklearn
Attribute selection methods- Gini Index and Entropy
Mathematics behind Decision trees and random forest
Boosting algorithms:- Adaboost, Gradient Boosting and XgBoost
Different Algorithms for Clustering
Different methods to deal with imbalanced data
Correlation Filtering
Variance Filtering
PCA & LDA
Content and Collaborative based filtering
Singular Value Decomposition
Different algorithms used for Time Series forecasting
Case studies

Requirements for this Course:

To make sense out of this course, you should be well aware of linear algebra, calculus, statistics, probability and python programming language.

Description:

Wild about Data Science and Machine Learning?

This course is an ideal fit for you.

This course will make you stride by venture into the universe of Machine Learning.

AI is the investigation of PC calculations that computerizes scientific model structure. It is a part of Artificial Intelligence dependent on the possibility that frameworks can gain from information, recognize examples and settle on choices with negligible human intercession.

AI is effectively being utilized today, maybe in a lot a bigger number of spots than one world anticipates.

It contains a ton of points and this course will cover all bit by bit.

This Machine Learning course will give you hypothetical just as useful information on Machine Learning.

This Machine Learning course is fun just as invigorating.

It will cover all normal and significant calculations and will give you the experience of dealing for certain genuine tasks.

This course will cover the accompanying points:-

Hypothesis and viable execution of direct relapse utilizing sklearn.
Hypothesis and viable execution of strategic relapse utilizing sklearn.
Element determination utilizing RFECV.
Information change with direct and strategic relapse.
Assessment measurements to investigate the exhibition of models
Industry significance of direct and strategic relapse.
Science behind KNN, SVM, and Naive Bayes calculations.
Execution of KNN, SVM, and Naive Bayes utilizing sklearn.
Quality determination techniques Gini Index and Entropy.
Science behind Decision trees and irregular backwoods.
Boosting calculations:- Adaboost, Gradient Boosting, and XgBoost.
Various calculations for bunching
Various strategies to manage imbalanced information.
Connection sifting
Change sifting
PCA and LDA
Content and Collaborative based sifting
Particular Value disintegration
Various calculations utilized for Time Series guaging.
Contextual investigations

Who this course is for:

Anyone who want to start a career in Machine Learning.
Students who have at least knowledge in linear algebra, calculus, statistics, probability and who want to start their journey in Machine Learning.
Any people who want to level up their Machine Learning Knowledge.
Software developers or programmers or Tech lover who want to change their career path to machine learning.
Technologists who are curious about how Machine Learning works in the real world.
Anyone who has already started their data science journey and now want to master in machine learning.
If you have no prior coding or scripting experience, This course is completely for you. This Course also includes Python Fundamental for beginners.