Learn Machine Learning From Scratch with Python

What you'll learn
Programming in Python
How to program a neural network
Libraries most used in Machine Learning
Solve practical problems applying Machine Learning techniques
Be able to Analyze the most common problems in Machine Learning
Reinforced
Learning Deep Learning

Requirements
Have a Will to Learn
Be a proactive person in Learning
Description
Everyone talks about Machine Learning but do we really understand what it is? What are the bases? How can we create our own algorithms? Why is it important to know it?

In this course we are going to explain the most important concepts that we must know about Machine Learning in a practical and fun way. We will progress little by little from simple concepts to more complex aspects, so that you are able to learn in an easy and intuitive way.

The course is designed so that you can learn from scratch, without the need to have prior knowledge about this world.

The course is structured as follows:

Basic Programming in Python, where we will see the basic aspects that you must handle in Python to complete the

Pandas Handling course , which will help us with all the previous data processing that we need to train our models of Machine learning

You will learn Numpy, a library widely used when working with vectors and matrices in Python.

Introduction to Machine Learning. In this Introduction section you will understand why it is important to know this technology that is revolutionizing the world and we will see application examples

. How is a Machine Learning model built? You will see step by step what is needed so that you can create your Machine Learning Algorithms

Supervised Learning, we will study what it is, how we can use it and we will implement an example from scratch using Python

Unsupervised Learning We will see some of the most used methods and we will implement some examples by doing use of popular libraries like Scikit Learn

Neural Networks. In this module we will explain what neural networks are and how we can implement them using popular libraries such as: TensorFlow, Keras and Scikit Learn. We will also see a real example of how to solve a classification problem in the fashion sector, applying neural networks with TensorFlow.

Reinforced Learning, We will introduce the basic concepts and we will see a simple example using Graphs.

Deep Learning, We will see a basic introduction to what Deep Learning is and we will implement our first example using convolutional neural networks.

Who this course is for:
People who want to learn about Machine Learning
Python developers with an interest in Machine Learning

HOMEPAGE

https://www.udemy.com/course/aprende-machine-learning-desde-cero-con-python/