Deep Learning Prerequisites: Logistic Regression in Python

Name: Deep Learning Prerequisites: Logistic Regression in Python
Brand: Udemy
SKU: 43509
Price: 12.99 USD
Availability: InStock

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Lazy Programmer Inc. 23 Machine Learning Udemy

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Reviews (8)

9.0/10 (Our Score)

Product is rated as #49 in category Machine Learning

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.

Instructor Details

Lazy Programmer Inc.Artificial intelligence and machine learning engineer

Votes: 1

Courses : 22

Today, I spend most of my time as an artificial intelligence and machine learning engineer with a focus on deep learning, although I have also been known as a data scientist, big data engineer, and full stack software engineer. I received my masters degree in computer engineering with a specialization in machine learning and pattern recognition. Experience includes online advertising and digital media as both a data scientist (optimizing click and conversion rates) and big data engineer (building data processing pipelines). Some big data technologies I frequently use are Hadoop, Pig, Hive, MapReduce, and Spark. I've created deep learning models to predict click-through rate and user behavior, as well as for image and signal processing and modeling text. My work in recommendation systems has applied Reinforcement Learning and Collaborative Filtering, and we validated the results using A/B testing. I have taught undergraduate and graduate students in data science, statistics, machine learning, algorithms, calculus, computer graphics, and physics for students attending universities such as Columbia University, NYU, Hunter College, and The New School. Multiple businesses have benefitted from my web programming expertise. I do all the backend (server), frontend (HTML/JS/CSS), and operations/deployment work. Some of the technologies I've used are: Python, Ruby/Rails, PHP, Bootstrap, jQuery (Javascript), Backbone, and Angular. For storage/databases I've used MySQL, Postgres, Redis, MongoDB, and more.

Specification: Deep Learning Prerequisites: Logistic Regression in Python

Duration	6 hours
Year	2020
Level	All
Certificate	Yes
Quizzes	Yes

8 reviews for Deep Learning Prerequisites: Logistic Regression in Python

4.4 out of 5

★★★★★

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★★★★★
William Richter – December 25, 2019
Want to understand some of the underlying theory behind deep learning. Course needs updated, all examples are in Python 2, which has an end of life on 1/1/2020. I can easily convert to Python 3 but those with limited experience may not be able to convert.
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★★★★★
MAK Khan – December 27, 2019
After following a few lectures that this is quite
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★★★★★
Michael Trimmel – January 3, 2020
H tte mir ein anderes Beispiel gew nscht E Commerce ist nicht mein Gebiet
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★★★★★
Rahul Dalal – January 7, 2020
I thought I knew Logistic Regression completely, but this course shed light on many important basics I had glossed over. Love the course.
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★★★★★
Aman Singh – January 9, 2020
a course with lots of mathematics to explain machine learning
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★★★★★
M Manish – January 26, 2020
Couldn’t expect anything more… The instructor here knows how to help us learn and he structured the course accordingly. I appreciate it a lot. Actually I needed a little more help in understanding Baye’s rule and MLE in general, in depth. I would take help of other sources for this. But, Great Job!!! and Great respect to the instructor. Thank you.
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★★★★★
Nathan Lou – March 29, 2020
insane
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★★★★★
David Gonz lez San Mart n – March 30, 2020
sometimes the teacher speaks very fast
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