Deep Learning Prerequisites: Logistic Regression in Python
Udemy Coupon Code for Deep Learning Prerequisites: Logistic Regression in Python Course. Data science, machine learning, and artificial intelligence in Python for students and professionals
Created by Lazy Programmer Inc. | 7 hours on-demand video course
Logistic Regression Course Overview
Deep Learning Prerequisites: Logistic Regression in Python
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.
This course is a lead-in to deep learning and neural networks – it covers a popular and fundamental technique used in machine learning, data science and statistics: logistic regression. We cover the theory from the ground up: derivation of the solution, and applications to real-world problems. We show you how one might code their own logistic regression module in Python.
This course does not require any external materials. Everything needed (Python, and some Python libraries) can be obtained for free.
This course provides you with many practical examples so that you can really see how deep learning can be used on anything. Throughout the course, we’ll do a course project, which will show you how to predict user actions on a website given user data like whether or not that user is on a mobile device, the number of products they viewed, how long they stayed on your site, whether or not they are a returning visitor, and what time of day they visited.
Another project at the end of the course shows you how you can use deep learning for facial expression recognition. Imagine being able to predict someone’s emotions just based on a picture!
If you are a programmer and you want to enhance your coding abilities by learning about data science, then this course is for you. If you have a technical or mathematical background, and you want use your skills to make data-driven decisions and optimize your business using scientific principles, then this course is for you.
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.
What you’ll learn
- program logistic regression from scratch in Python
- describe how logistic regression is useful in data science
- derive the error and update rule for logistic regression
- understand how logistic regression works as an analogy for the biological neuron
- use logistic regression to solve real-world business problems like predicting user actions from e-commerce data and facial expression recognition
- understand why regularization is used in machine learning
- Understand important foundations for OpenAI ChatGPT, GPT-4, DALL-E, Midjourney, and Stable Diffusion
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Logistic Regression in Python Course Reviews
Everything You Need to Know About Deep Learning Prerequisites: Logistic Regression in Python
This course offers a comprehensive and well-structured introduction to Deep Learning Prerequisites. Lazy Programmers, the instructor, brings a wealth of expertise in IT & Software, making this course both informative and engaging.
The course structure is easy to follow. Each section, for example, covers a different aspect of Deep Learning Prerequisites Course, ensuring a logical progression through the material. It includes video lectures, readings, and hands-on exercises, which make complex concepts accessible and practical.
Moreover, The Instructors explains each topic clearly and concisely. He supports the lessons with plenty of examples and exercises, which help students grasp the material effectively.
What I appreciated most about this course is its practical focus. For instance, the instructor emphasizes teaching skills and knowledge that are directly applicable to real-world scenarios. Additionally, students gain access to helpful resources such as templates, checklists, and cheat sheets.
Another standout feature is the platform itself. Udemy Coupons offers flexibility, allowing students to learn at their own pace and access course materials from anywhere with an internet connection. Furthermore, the multiple payment options make it easy for students to choose a plan that suits their budget.
In addition, the course community is highly active, with forums where students can ask questions and engage with peers. The instructor, consequently, is very responsive and addresses student inquiries and feedback promptly.
Overall, I highly recommend the Deep Learning Prerequisites: Logistic Regression in Python to anyone looking to learn Logistic Regression This well-organized and practical course equips you with the skills and knowledge you need to succeed in this field.
