Machine Learning

5 Challenges in Machine Learning Adoption and How to Overcome Them

Image by Author | Created on Canva Machine learning presents transformative opportunities for businesses and organizations across various industries. From improving customer experiences to optimizing operations and driving innovation, the applications of machine learning are vast. However, adopting machine learning solutions is not without challenges. These challenges span across data quality, technical complexities, infrastructure requirements, and cost constraints amongst others. Understanding these challenges is important to come up with effective strategies to adopt ML solutions. Challenges in ML Adoption | […]

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Machine Learning

Introduction to AutoML: Automating Machine Learning Workflows

Image by Author AutoML is a tool designed for both technical and non-technical experts. It simplifies the process of training machine learning models. All you have to do is provide it with the dataset, and in return, it will provide you with the best-performing model for your use case. You don’t have to code for long hours or experiment with various techniques; it will do everything on its own for you. In this tutorial, we will learn about AutoML and […]

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Algorithms Leave a comment

Tracing the path to self-adapting AI agents

The games industry has long been a frontier of innovation for AI. In the early 2000s, programmers hand-coded neural networks to breathe life into virtual worlds (opens in new tab), creating engaging AI characters (opens in new tab) that interact with players. Fast forward two decades, neural networks have grown from their humble beginnings to colossal architectures with billions of parameters, powering real-world applications like

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Python

Quiz: Python Protocols: Leveraging Structural Subtyping

Interactive Quiz ⋅ 11 QuestionsBy Leodanis Pozo Ramos Share Or copy the link: Copied! Happy Pythoning! Test your understanding of how to create and use Python protocols while providing type hints for your functions, variables, classes, and methods. Take this quiz after reading our Python Protocols: Leveraging Structural Subtyping tutorial. The quiz contains 11 questions and there is no time limit. You’ll get 1 point for each correct answer. At    

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Python

Quiz: Logging in Python

Interactive Quiz ⋅ 9 QuestionsBy Philipp Acsany Share Or copy the link: Copied! Happy Pythoning! In this quiz, you’ll test your understanding of Python’s logging module. Logging is a very useful tool in a programmer’s toolbox. It can help you develop a better understanding of the flow of a program and discover scenarios that you might not have thought of while developing. Logs provide developers with an extra set of eyes that are constantly looking    

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Python

Quiz: Hugging Face Transformers

Interactive Quiz ⋅ 6 QuestionsBy Bartosz Zaczyński Share Or copy the link: Copied! Happy Pythoning! In this quiz, you’ll test your understanding of Hugging Face Transformers. This library is a popular choice for working with transformer models in natural language processing tasks, computer vision, and other machine learning applications. The quiz contains 6 questions and there is no time limit. You’ll get 1 point for each correct answer. At the    

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Python

Hugging Face Transformers: Leverage Open-Source AI in Python

Transformers is a powerful Python library created by Hugging Face that allows you to download, manipulate, and run thousands of pretrained, open-source AI models. These models cover multiple tasks across modalities like natural language processing, computer vision, audio, and multimodal learning. Using pretrained open-source models can reduce costs, save the time needed to train models from scratch, and give you more control over the models you deploy. Throughout this tutorial, you’ll gain a conceptual understanding of Hugging Face’s AI offerings and learn how to […]

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Neural Machine Translation (NMT), NMT Leave a comment

Lessons learned from analyzing values in multilingual encoders and what it means for LLMs

This post is a hindsight on two studies on multilingual sentence embeddings we published a year ago and comments on what I think people analyzing LLMs today should take away from them. In late 2022, we (which mainly was the work of Kathy Hämmerl from Munich and Björn Diesenroth and Patrick Schramowski from Darmstadt) finished a paper called Speaking Multiple Languages Affects the Moral Bias of Language Models (later published in Findings of ACL 2023) where we tried to compare […]

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Python

pandas GroupBy: Grouping Real World Data in Python

Whether you’ve just started working with pandas and want to master one of its core capabilities, or you’re looking to fill in some gaps in your understanding about .groupby(), this course will help you to break down and visualize a pandas GroupBy operation from start to finish. This course is meant to complement the official pandas documentation and the pandas Cookbook, where there are self-contained, bite-sized examples. Here, however, you’ll focus on three more involved walkthroughs that use real-world datasets. […]

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Machine Learning

Understanding LangChain LLM Output Parser

The large Language Model, or LLM, has revolutionized how people work. By helping users generate the answer from a text prompt, LLM can do many things, such as answering questions, summarizing, planning events, and more. However, there are times when the output from LLM is not up to our standard. For example, the text generated could be thoroughly wrong and need further direction. This is where the LLM Output Parser could help. By standardizing the output result with LangChain Output […]

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