Complete Machine Learning & Data Science with Python | A-Z (Udemy.com)

Hello there,
Welcome to the “Complete Machine Learning & Data Science with Python | A-Z” course
Use Scikit, learn NumPy, Pandas, Matplotlib, Seaborn, and dive into machine learning A-Z with Python and Data Science, global conflict project, global conflict data analysis, real-world data science project

Machine learning isn’t just useful for predictive texting or smartphone voice recognition Machine learning is constantly being applied to new industries and new problems Whether you’re a marketer, video game designer, or programmer, my course on OAK Academy here to help you apply machine learning to your work Complete machine learning & data science with python | a-z, machine learning a-z, Complete machine learning & data science with python, complete machine learning and data science with python a-z, machine learning using python, complete machine learning and data science, machine learning, complete machine learning, data science
It’s hard to imagine our lives without machine learning Predictive texting, email filtering, and virtual personal assistants like Amazon’s Alexa and the iPhone’s Siri, are all technologies that function based on machine learning algorithms and mathematical models Python, machine learning, django, python programming, machine learning python, python for beginners, data science
Python instructors on OAK Academy specialize in everything from software development to data analysis, and are known for their effective, friendly instruction for students of all levels
Whether you work in machine learning or finance, or are pursuing a career in web development or data science, Python is one of the most important skills you can learn Python's simple syntax is especially suited for desktop, web, and business applications Python's design philosophy emphasizes readability and usability Python was developed upon the premise that there should be only one way (and preferably one obvious way) to do things, a philosophy that has resulted in a strict level of code standardization The core programming language is quite small and the standard library is also large In fact, Python's large library is one of its greatest benefits, providing a variety of different tools for programmers suited for many different tasks

Do you know data science needs will create 11 5 million job openings by 2030?

Do you know the average salary is $100 000 for data science careers!

Data Science Careers Are Shaping The Future

Data science experts are needed in almost every field, from government security to dating apps Millions of businesses and government departments rely on big data to succeed and better serve their customers So data science careers are in high demand

• If you want to learn one of the employer’s most request skills?

• If you are curious about Data Science and looking to start your self-learning journey into the world of data with Python?

• If you are an experienced developer and looking for a landing in Data Science!

In all cases, you are at the right place!

We've designed for you “Complete Machine Learning & Data Science with Python | A-Z” a straightforward course for Python Programming Language and Machine Learning

In the course, you will have down-to-earth way explanations with projects With this course, you will learn machine learning step-by-step I made it simple and easy with exercises, challenges, and lots of real-life examples

We will open the door of the Data Science and Machine Learning a-z world and will move deeper You will learn the fundamentals of Machine Learning A-Z and its beautiful libraries such as Scikit Learn. Plus, you will get hands-on experience by completing a real-world Global Conflict Data Analysis Project at the end of the course!

Throughout the course, we will teach you how to use Python to analyze data, create beautiful visualizations, and use powerful machine learning python algorithms

This Machine Learning course is for everyone!

My "Machine Learning with Hands-On Examples in Data Science" is for everyone! If you don’t have any previous experience, not a problem! This course is expertly designed to teach everyone from complete beginners, right through to professionals ( as a refresher)

Why we use a Python programming language in Machine learning?

Python is a general-purpose, high-level, and multi-purpose programming language The best thing about Python is, it supports a lot of today’s technology including vast libraries for Twitter, data mining, scientific calculations, designing, back-end server for websites, engineering simulations, artificial learning, augmented reality and what not! Also, it supports all kinds of App development

What you will learn?

In this course, we will start from the very beginning and go all the way to the end of "Machine Learning" with examples

Before each lesson, there will be a theory part After learning the theory parts, we will reinforce the subject with practical examples

During the course you will learn the following topics:

• What is Machine Learning?

• More About Machine Learning

• Machine Learning Terminology

• Evaluation Metrics

• What is Classification vs Regression?

• Evaluating Performance-Classification Error Metrics

• Evaluating Performance-Regression Error Metrics

• Machine Learning with Python

• Supervised Learning

• Cross-Validation and Bias Variance Trade-Off

• Use Matplotlib and seaborn for data visualizations

• Machine Learning with SciKit Learn

• Linear Regression Theory

• Logistic Regression Theory

• Logistic Regression with Python

• K Nearest Neighbors Algorithm Theory

• K Nearest Neighbors Algorithm With Python

• K Nearest Neighbors Algorithm Project Overview

• K Nearest Neighbors Algorithm Project Solutions

• Decision Trees And Random Forest Algorithm Theory

• Decision Trees And Random Forest Algorithm With Python

• Decision Trees And Random Forest Algorithm Project Overview

• Decision Trees And Random Forest Algorithm Project Solutions

• Support Vector Machines Algorithm Theory

• Support Vector Machines Algorithm With Python

• Support Vector Machines Algorithm Project Overview