MP4 | Video: h264, 1280×720 | Audio: AAC, 44.1 KHz
Language: English | Size: 2.52 GB | Duration: 2h 56m
Advanced Machine Learning In Python Programming Language
Advanced Machine Learning In Python Programming Language
What you’ll learn
Fundamentals about Machine Learning & how it is better than conventional automations
Starting From What Is Machine Learning To Practical Implementation
Covers Detailed Concept Of All ML Models & Algorithms-Basic To Adv
How To Build Your ML Models On Real Data Set
Fine tuning Of The Models For Better Accuracy & Prediction
Understanding The Parameters Of All Kinds Of ML Models
Steps Involved In ML Model Building & Important Terms
How To improve The Accuracy Using Advance Techniques .
Important Model Evaluation Metrics & Important Resources
Requirements
Student should have a fair idea about Python Programming Language and Google Colab IDE
Student should be familiar with the basic ML Model building and statistics behind that.
Description
Learn the hands-on tutorial on Advance Machine Learning Algorithms like GBM, AddaBoosting techniques, XGBoost, and many more.This Course Will Give You A Precise Approach To Machine Learning
Starting From What Is Machine Learning To Practical Implementation
Covers Detailed Concept Of All ML Models & Algorithms-Basic To Adv.
How To Build Your ML Models On Real Data Set.
Fine-tuning Of The Models For Better Accuracy & Prediction.
Understanding The Parameters Of All Kinds Of ML Models.
Steps Involved In ML Model Building & Important Terms.
Machine Learning In MS Excel, Python & R Prog. Lang.
Salary Structure And Role Of ML Practitioner.
How To Improve Accuracy Using Advance Techniques.
Important Model Evaluation Metrics & Important Resources
Learn the Applied Data Science and Machine Learning, get hired and have fun along the way with the most modern, up-to-date Data Science course on Udemy (we use the latest version of Python, Tensorflow 2.0 and other libraries). This course is focused on efficiency: never spend time on confusing, out of date, incomplete Machine Learning tutorials anymore. We are pretty confident that this is the most comprehensive and modern course you will find on the subject anywhere (bold statement, we know).
This comprehensive and project-based course will introduce you to all of the modern skills of a Data Scientist and along the way, we will build many real-world projects to add to your portfolio. You will get access to all the code, workbooks, so that you can put them on your portfolio right away! We believe this course solves the biggest challenge to entering the Data Science and Machine Learning field: having all the necessary resources in one place and learning the latest trends and on-the-job skills that employers want.
The curriculum is going to be very hands-on as we walk you from start to finish about becoming a professional Machine Learning and Data Science engineer.
The topics covered in this course are
Let’s Understand Machine Learning In Details
Everything You Need To Know About ML Before Getting Started
General Approach To All ML Model Building
Overview To Advance ML Models
Facts About Adv ML Models
Fundamentals About Gradient Boosting Technique
Hands On Tutorial- GBM With Python
Intro To AddaBoost
AddaBoost Working Principle
AddaBoost With Python
XGBoost Overview, Intro
XGBoost Parameters
XGBoost With Python-Part 1
XGBoost With Python-Part 2
XGBoost With Python-Part 3
XGBoost Conclusion
By the end of this course, you will be a complete Data Scientist that can get hired at large companies. We are going to use everything we learn in the course to build professional real world projects. By the end, you will have a stack of projects you have built that you can show off to others.
Here’s the truth: Most courses teach you Data Science and do just that. They show you how to get started. But the thing is, you don’t know where to go from there or how to build your own projects. Or they show you a lot of code and complex math on the screen, but they don’t really explain things well enough for you to go off on your own and solve real-life machine learning problems.
Whether you are new to programming, or want to level up your Data Science skills, or are coming from a different industry, this course is for you. This course is not about making you just code along without understanding the principles so that when you are done with the course you don’t know what to do other than watch another tutorial. No! This course will push you and challenge you to go from a beginner in Data Science experience to someone that can go off to advance model building.
Machine Learning has applications in Business Marketing and Finance, Healthcare, Cybersecurity, Retail, Transportation and Logistics, Agriculture, Internet of Things, Gaming and Entertainment, Patient Diagnosis, Fraud Detection, Anomaly Detection in Manufacturing, Government, Academia/Research, Recommendation Systems and so much more. The skills learned in this course are going to give you a lot of options for your career.
You hear statements like Artificial Neural Network, or Artificial Intelligence (AI), and by the end of this course, you will finally understand what these mean!
Who this course is for
Intermediate & Advance Machine Learning Enthusiasts
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