Applications: decrypting ciphers, spam detection, sentiment analysis, article spinners, and latent semantic analysis.

RS 599

What Will I Learn?

- Write your own cipher decryption algorithm using genetic algorithms and language modeling with Markov models
- Write your own sentiment analysis code in Python
- Have an idea of how to write your own article spinner in Python
- Write your own spam detection code in Python
- Perform latent semantic analysis or latent semantic indexing in Python
- Understand important foundations for OpenAI ChatGPT, GPT-4, DALL-E, Midjourney, and Stable Diffusion

Curriculum For This Course

3 Sections
12 Lessons
01:42:12 Hours

Course Content

1 Lessons
00:05:29 Hours

- Natural Language Processing what is it used for? 00:05:29 Preview

Machine Learning Basic Review

6 Lessons
00:56:15 Hours

- Machine Learning: Section Introduction 00:07:52
- What is Classification? 00:07:51
- What is Regression? 00:07:19
- What is a Feature Vector 00:06:49
- Machine Learning is Nothing but Geometry 00:04:51
- Comparing Different Machine Learning Models 00:21:33

Markov Models

5 Lessons
00:40:28 Hours

- Markov Models Section Introduction 00:04:46
- The Markov Property 00:15:24
- The Markov Model 00:09:24
- Probability Smoothing and Log-Probabilities 00:07:51
- Building a Text Classifier (Theory) 00:03:03

Requirements

- Install Python, it's free!
- You should be at least somewhat comfortable writing Python code
- Know how to install numerical libraries for Python such as Numpy, Scipy, Scikit-learn, Matplotlib, and BeautifulSoup
- Take my free Numpy prerequisites course (it's FREE, no excuses!) to learn about Numpy, Matplotlib, Pandas, and Scikit-Learn, as well as Machine Learning basics
- Optional: If you want to understand the math parts, linear algebra and probability are helpful

+ View More

Description

Ever wondered how AI technologies like **OpenAI** **ChatGPT**,** GPT-4**, **DALL-E**, **Midjourney**, and **Stable Diffusion** really work? In this course, you will learn the foundations of these groundbreaking applications.

In this course you will build MULTIPLE practical systems using natural language processing, or NLP - the branch of machine learning and data science that deals with text and speech. This course is not part of my deep learning series, so it doesn't contain any hard math - just straight up coding in Python. All the materials for this course are FREE.

After a brief discussion about what NLP is and what it can do, we will begin building very useful stuff. The first thing we'll build is a **cipher decryption algorithm**. These have applications in warfare and espionage. We will learn how to build and apply several useful NLP tools in this section, namely, **character-level language models (using the Markov principle)**, and **genetic algorithms**.

The second project, where we begin to use more traditional "**machine learning**", is to build a **spam detector**. You likely get very little spam these days, compared to say, the early 2000s, because of systems like these.

Next we'll build a model for **sentiment analysis **in Python. This is something that allows us to assign a score to a block of text that tells us how positive or negative it is. People have used sentiment analysis on Twitter to **predict the stock market**.

We'll go over some practical tools and techniques like the NLTK (natural language toolkit) library and latent semantic analysis or LSA.

Finally, we end the course by building an **article spinner**. This is a very hard problem and even the most popular products out there these days don't get it right. These lectures are designed to just get you started and to give you ideas for how you might improve on them yourself. Once mastered, you can use it as an SEO, or search engine optimization tool. Internet marketers everywhere will love you if you can do this for them!

This course focuses on "**how to build and understand**", not just "how to use". Anyone can learn to use an API in 15 minutes after reading some documentation. It's not about "remembering facts", it's about **"seeing for yourself" via experimentation**. It will teach you how to visualize what's happening in the model internally. If you want **more** than just a superficial look at machine learning models, this course is for you.

"If you can't implement it, you don't understand it"

Or as the great physicist Richard Feynman said: "What I cannot create, I do not understand".

My courses are the ONLY courses where you will learn how to implement machine learning algorithms from scratch

Other courses will teach you how to plug in your data into a library, but do you really need help with 3 lines of code?

After doing the same thing with 10 datasets, you realize you didn't learn 10 things. You learned 1 thing, and just repeated the same 3 lines of code 10 times..

**1**Reviews**51**Courses

+ View More

Hello, my name is Victor Kercado. I'm a successful podcaster and life coach in the area of personal growth. I've been fortunate to help many people improve their lives thru mindfulness, communication, and spirituality. I look forward to sharing my knowledge with you thru courses that will inspire and motivate you to improve in all areas of your life. Thank you for listening!

RS 599

## Write A Public Review