Natural Language Processing (NLP) and ML within 100% Snowflake using Snowpark Python
Opinions expressed in this post are solely my own and do not represent the views or opinions of my employer.
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My Data Science Internship Experience at Trendyol
Trendyol Data Science Team from a Intern’s Perspective How my Journey Began Hi! My name’s Okan and I am currently doing an internship at Trendyol, a leading international e-commerce platform founded in Turkey.
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SOAR Development with Python
GitHub – anil-yelken/SOAR: SOAR SOAR stands for “Security Orchestration, Automation and Incident Response”. The SOAR solution is technology that uses… github.com
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How I used artificial intelligence to publish an illustrated children’s book in 24 hours
As someone who loves stories, I’ve always dreamt of publishing my own. One of the stories I created is about five naughty little bugs — a story my children love to hear (again… and again… and again). A week ago I came across DALL·E 2 which sparked my curiosity.
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Data is not the new oil! Lessons in evolving a Data Platform
Our data platform has been running for years. We hired a bunch of data scientist and engineers, too many unused tables which are running constant pipelines. The value we get from it is not enough to justify the investment we’ve made.
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Python 3.11 — new features and improvements
A quick look at recently released python 3.11 features
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How to Get the First Match From a Python List or Iterable
At some point in your Python journey, you may need to find the first item that matches a certain criterion in a Python iterable, such as a list or dictionary. The simplest case is that you need to confirm that a particular item exists in the iterable. For example, you want to find a name in a list of names or a substring inside a string. In these cases, you’re best off using the in operator. However, there are many […]
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Why Attention is all you need: Why, When, What (Part 1)
“Computers are incredibly fast, accurate and stupid; humans are incredibly slow, inaccurate, and brilliant; together they are powerful beyond imagination.” Albert Einstein From detecting Spam emails to chatting with Bots messages through your favorite social media application, the use of Natural Language Processing (NLP) has been huge.
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Apply 100 ML Models with Hyperparameter tuning using 3 lines of code
Auto-sklearn library gives you the ability to apply bulk ML Models on your dataset along with changing and finding best hyperparameter for that model. The only disadvantage is that it is not available for windows users, but since I am also a windows user so to overcome this problem, I recommend you use google colab, Kaggle, or Docker. There you can easily install the auto-sklearn library.
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