Data Science: Supervised Machine Learning in Python

Name: Data Science: Supervised Machine Learning in Python
Brand: Udemy
SKU: 43914
Price: 12.99 USD
Availability: InStock

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Lazy Programmer Inc. 18 Machine Learning Udemy

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Reviews (6)

8.4/10 (Our Score)

Product is rated as #160 in category Machine Learning

In recent years, we’ve seen a resurgence in AI, or artificial intelligence, and machine learning.

Machine learning has led to some amazing results, like being able to analyze medical images and predict diseases on–par with human experts.

Google’s AlphaGo program was able to beat a world champion in the strategy game go using deep reinforcement learning.

Machine learning is even being used to program self driving cars, which is going to change the automotive industry forever. Imagine a world with drastically reduced car accidents, simply by removing the element of human error.

Google famously announced that they are now machine learning first , meaning that machine learning is going to get a lot more attention now, and this is what’s going to drive innovation in the coming years. It’s embedded into all sorts of different products.

Machine learning is used in many industries, like finance, online advertising, medicine, and robotics.

It is a widely applicable tool that will benefit you no matter what industry you’re in, and it will also open up a ton of career opportunities once you get good.

Machine learning also raises some philosophical questions. Are we building a machine that can think? What does it mean to be conscious? Will computers one day take over the world?

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: Data Science: Supervised Machine Learning in Python

Duration	6 hours
Year	2020
Level	Beginner
Certificate	Yes
Quizzes	No

6 reviews for Data Science: Supervised Machine Learning in Python

4.2 out of 5

★★★★★

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★★★★★
Sushant Jain – January 15, 2020
Lack of live examples
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★★★★★
Josefine Svegborn – February 4, 2020
This course delivers on its promises. The teacher goes straight to the point and explains complex theory in a concise way without leaving too many stones unturned. My only issue is the fact that the teacher expects the student to figure out all associated setup by themselves and the same expectations are shown in his QA answers (where he points to resources rather than providing direct answers). This seem to be his teaching philosophy however, which he had good arguments for (in the Appendix). It’s just not my favourite approach as I think it’s more time consuming than useful at times. The course is well worth the price!
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★★★★★
Charles Long – March 20, 2020
Excellent course and one that’ll I’ll refer back to over and over again. Really like the way underlying mathematics was explained for models.
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★★★★★
Kishore Suresh – March 26, 2020
Lot to learn. Need re learn course several times once I start using these concepts in practical scenario.
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★★★★★
Albert R Djomegni – March 30, 2020
Still on my way
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★★★★★
Pooya.Row – July 29, 2020
Too many pauses
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