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Deep Learning Prerequisites: Logistic Regression in Python

Udemy
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Udemy – Deep Learning Prerequisites: Logistic Regression in Python Course. Data science, machine learning, and artificial intelligence in Python for students and professionals

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Deep Learning Prerequisites: Logistic Regression in Python Course

Description

This Deep Learning Prerequisites: Logistic Regression in Python 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 Deep Learning Prerequisites course does not require any external materials. Everything needed (Python, and some Python libraries) can be obtained for free. This Deep Learning Prerequisites: Logistic Regression in Python 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.

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Logistic Regression in Python Online Courses

What things to 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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Who this course is for:

This training suits people who :
  • Adult learners who want to get into the field of data science and big data
  • Students who are thinking of pursuing machine learning or data science
  • Students who are tired of boring traditional statistics and prewritten functions in R, and want to learn how things really work by implementing them in Python
  • People who know some machine learning but want to be able to relate it to artificial intelligence
  • People who are interested in bridging the gap between computational neuroscience and machine learning
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Specifications Deep Learning Prerequisites: Logistic Regression in Python

Course Information
  • Publisher : Udemy
  • Instructor : Lazy Programmer Inc
  • Language : English
  • Level of training : from beginners to advanced
  • Duration Time : 7 hours
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Courses Reviews: Deep Learning in Python Prerequisites

Find helpful customer reviews and review ratings for Deep Learning Prerequisites: Logistic Regression in Python
9.8Expert Score
Awesome

As usual, this professor knocked it out of the park. His mathematical representations of the content without using scikit learn made it possible to understand what it going on behind the curtain. Highly recommend this professor and his content; I will be buying more courses from him.

Positive
  • This course makes it really easy to start machine learning. Even if you don't have any prior experience you can just simply get started from the first tutorial you look at. I am a slow learner, so this course is perfect for me whilst I work full time.
  • This course introduced the concept of logistic regression, where the student learns how neural networks are built from neurons.
  • Very good course. Interesting content and I liked the facial recognition project. The Q&A was very helpful. Would recommend 5/5 stars.
Negatives
  • I want a course from you where you give statistics and probability and put in python terms as well.. Except that I love the course, but it took more than 2-3 weeks to finish the course.
  • The course goes into the ground of Logistic Regression. I felt sometimes as not everything is exhaustively explained. This on the other hand makes you think more.
Josh Smith
Josh Smith

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