ML Journal 17 — NLP — BLOOM for medical diagnosis (1/?)
2022/10/28 I am still really struggling not to procrastinate. I will try my best and put in minimal work every day. I was initially going to make
Read moreDeep Learning, NLP, NMT, AI, ML
2022/10/28 I am still really struggling not to procrastinate. I will try my best and put in minimal work every day. I was initially going to make
Read moreGoogle Image (NLP)
Read moreSamia S. Azim1, Varun Aggrawal2, and Dharmendra Sarsawat3 1Department of Computer Science, Institute of Business Administration Karachi 2Elmore School of Electrical and Computer Engineering
Read moreAre you interested in writing usage examples for your code that work as documentation and test cases simultaneously? If your answer is yes, then Python’s doctest module is for you. This module provides a testing framework that doesn’t have too steep a learning curve. It’ll allow you to use code examples for two purposes: documenting and testing your code. Apart from allowing you to use your code’s documentation for testing the code itself, doctest will help you keep your code […]
Read moreOf late, we’ve been hearing about Twitter bots in the news due to the whole saga of Elon Musk buying Twitter. One of the reasons the deal took so long to pan out was Musk’s concerns about the number of spam bots running rampant on the platform. While Musk believes that bots make up more than 20% of accounts on Twitter, Twitter states that the number of bots on its platform is marginal. So, what’s this Twitter bot thing? A […]
Read more“Stop using AI.” This is how Dr. Kavita Ganesan, an AI expert since 2005, begins her book The Business Case for AI. In a refreshingly direct tone, Ganesan goes on to deliver the news that, yes, you probably need to rethink your use of AI and, no, it does not need to be this difficult or this expensive. While AI is a necessary tool for businesses to remain competitive, many find themselves worried about the investment, and the consequences– what […]
Read morePrecision and recall are commonly used metrics to measure the performance of machine learning models or AI solutions in general. It helps understand how well models are making predictions. Let’s use an email SPAM prediction example. Say you have a model that looks at an email and decides whether it’s SPAM or NOT SPAM. To see how well it’s doing, you want to compare it with human-generated labels, which we will call the actual labels. To demonstrate this, the table […]
Read morePart 4: Exploring the hasnans, dtype and iat attributes of Series data structure.
Read moreI’ve been programming for about 20 years now, and my “aha moment” with python came to me last night. It was a pretty simple one — I started with Python 2 because that’s what we’re using at work (and it was free). But after some trial and error, I figured out how to get started quickly with Python 3.
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