Python Programming: Machine Learning, Deep Learning | Python (Udemy.com)

Hello there,
Welcome to the “Python Programming: Machine Learning, Deep Learning | Python” course

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Python Machine Learning and Python Deep Learning with Data Analysis, Artificial Intelligence, OOP, and Python Projects

Complete hands-on deep learning tutorial with Python Learn Machine Learning Python, go from zero to hero in Python 3

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
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, this course is here to help you apply machine learning to your work
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 programming: machine learning deep learning | python, python programming: machine learning deep learning, machine learning python, deep learning, machine learning, deep learning python, python programming machine learning deep learning, python programming machine learning, oak academy, python

In this course, we will learn what is Deep Learning and how does it work

This course has suitable for everybody who interested in Machine Learning and Deep Learning concepts in Data Science

First of all, in this course, we will learn some fundamental stuff of Python and the Numpy library These are our first steps in our Deep Learning journey After then we take a little trip to Machine Learning Python history Then we will arrive at our next stop Machine Learning in Python Programming Here we learn the machine learning concepts, machine learning a-z workflow, models and algorithms, and what is neural network concept After then we arrive at our next stop Artificial Neural network And now our journey becomes an adventure In this adventure we'll enter the Keras world then we exit the Tensorflow world Then we'll try to understand the Convolutional Neural Network concept But our journey won't be over Then we will arrive at Recurrent Neural Network and LTSM We'll take a look at them After a while, we'll trip to the Transfer Learning concept And then we arrive at our final destination Projects in Python Bootcamp Our play garden Here we'll make some interesting machine learning models with the information we've learned along our journey

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

The Logic of Machine Learning such as Machine Learning models and algorithms, Gathering data, Data pre-processing, Training and testing the model etc

Before we start this course, we will learn which environments we can be used for developing deep learning projects

During the course you will learn:

1. Fundamental stuff of Python and its library Numpy

2. What is the Artificial Intelligence (Ai), Machine Learning, and Deep Learning

3. History of Machine Learning

4. Turing Machine and Turing Test

5. The Logic of Machine Learning such as

   • Understanding the machine learning models

   • Machine Learning models and algorithms

   • Gathering data

   • Data pre-processing

   • Choosing the right algorithm and model

   • Training and testing the model

   • Evaluation

6. Artificial Neural Network with these topics

   • What is ANN

   • Anatomy of NN

   • Tensor Operations

   • The Engine of NN

   • Keras

   • Tensorflow

7. Convolutional Neural Network

8. Recurrent Neural Network and LTSM

9. Transfer Learning

10. Reinforcement Learning