ODSC - Open Data Science

MARCH 6, 2024

For instance, two major Machine Learning tasks are Classification, where the goal is to predict a label, and Regression, where the goal is to predict continuous values. REGISTER NOW Building upon the exponential advancements in Deep Learning, Generative AI has attained mastery in Natural Language Processing.

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Mlearning.ai

MARCH 9, 2023

In this article, we investigate the robustness of the Markov Blanket Discovery (MBD) approach to adversarial attacks in image segmentation, aiming to contribute to the development of more reliable and secure image segmentation algorithms. 2018; Sitawarin et al., 2018; Papernot et al., 2018; Papernot et al.,

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ODSC - Open Data Science

APRIL 17, 2023

Minor changes in the input data that are very apparent to human intelligence are not so for deep learning models. Deep learning is essentially matrix multiplication, which means even small perturbations in the coefficients can cause a significant change in the output.

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Mlearning.ai

FEBRUARY 10, 2023

In the previous articles, we saw there are two main components of error, called avoidable bias and variance. In this article, we will see how to address them. In the big data and deep learning era, now you have much more flexibility. Machine learning yearning. machine-learning-yearning-book (2017). [2].

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Mlearning.ai

APRIL 8, 2023

In this article, we’ll look at the evolution of these state-of-the-art (SOTA) models and algorithms, the ML techniques behind them, the people who envisioned them, and the papers that introduced them. Evolution of SOTA models in NLP and factors affecting them Here is the evolutionary map for this article.

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PyImageSearch

NOVEMBER 13, 2023

Home Table of Contents Faster R-CNNs Object Detection and Deep Learning Measuring Object Detector Performance From Where Do the Ground-Truth Examples Come? One of the most popular deep learning-based object detection algorithms is the family of R-CNN algorithms, originally introduced by Girshick et al.

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Towards AI

JULY 23, 2023

In this article, we aim to focus on the development of one of the most powerful generative NLP tools, OpenAI’s GPT. Step 1: We highlight the points from different articles to make a set of useful information. The authors introduced the idea of transfer learning in the natural language processing, understanding, and inference world.

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Heartbeat

MARCH 22, 2023

This week, we’ve got some fantastic pieces on NLP, including a discussion of RoBERTa, and some deep dives into computer vision. We’ve got a lot of great articles lined up as well so be sure to subscribe to Heartbeat and your favorite authors to stay up-to-date!

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Towards AI

FEBRUARY 10, 2023

In this article, I aim to bring attention to the importance of knowing that, even though large AI models are impressive, there are often unacknowledged costs behind them. China’s data center industry gets 73% of its power from coal, emitting roughly 99 million tons of CO2 in 2018 [4].

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ODSC - Open Data Science

MARCH 22, 2023

Cleanlab has been used to find millions of label errors in the most famous ML datasets: [link] In this Towards AI article , an XGBoost model was trained on a tabular dataset of student grades that had mislabeled examples, achieving 79% accuracy on a test set with validated labels.

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Heartbeat

MARCH 15, 2023

An open-source machine learning model called BERT was developed by Google in 2018 for NLP, but this model had some limitations, and due to this, a modified BERT model called RoBERTa (Robustly Optimized BERT Pre-Training Approach) was developed by the team at Facebook in the year 2019. The library can be installed via pip.

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Mlearning.ai

JULY 31, 2023

The Art of Turning Data Into Language This article is part of a series about the Transformer architecture. If you haven’t read the others, refer to the introductory article here. Yin and Shen (2018) accompany their research with a code implementation on GitHub here. Likewise, sound and text have no meaning to a computer.

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Towards AI

JULY 20, 2023

An additional 2018 study found that each SLR takes nearly 1,200 total hours per project. New research has also begun looking at deep learning algorithms for automatic systematic reviews, According to van Dinter et al. used ML and NLP to generate automatic summaries of full-text articles, achieving high rates of recall (91.2%

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Mlearning.ai

MAY 8, 2023

A comprehensive step-by-step guide with data analysis, deep learning, and regularization techniques Introduction In this article, we will use different deep-learning TensorFlow neural networks to evaluate their performances in detecting whether cell nuclei mass from breast imaging is malignant or benign.

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Data Science Dojo

AUGUST 16, 2023

Transformer models are a type of deep learning model that are used for natural language processing (NLP) tasks. They are able to learn long-range dependencies between words in a sentence, which makes them very powerful for tasks such as machine translation, text summarization, and question answering.

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Data Science Dojo

AUGUST 16, 2023

Transformer models are a type of deep learning model that are used for natural language processing (NLP) tasks. They are able to learn long-range dependencies between words in a sentence, which makes them very powerful for tasks such as machine translation, text summarization, and question answering.

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Heartbeat

FEBRUARY 6, 2023

We will also examine these algorithms in the following stages of the article. YOLOv3 is a newer version of YOLO and was released in 2018. You can follow my Medium account , and if you like the article, you can present your appreciation with claps. You can also follow and communicate with me on social media.

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Flipboard

AUGUST 25, 2023

“They will be right if you define any form of machine learning to be AI.” (An An MIT article defines machine learning as a machine’s ability to “imitate intelligent human behavior.”) The “deep learning revolution” — a time when development and use of the technology exploded — took off around 2014, Zhavoronkov said.

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Mlearning.ai

FEBRUARY 19, 2023

It combines techniques from computational linguistics, probabilistic modeling, deep learning to make computers intelligent enough to grasp the context and the intent of the language. GPT-3 is a successor to the earlier GPT-2 (released in Feb 2019) and GPT-1 (released in June 2018) models . Hope you like it!

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ODSC - Open Data Science

SEPTEMBER 21, 2023

After all, this is what machine learning really is; a series of algorithms rooted in mathematics that can iterate some internal parameters based on data. This is understandable: a report by PwC in 2018 suggested that 30% of UK jobs will be impacted by automation by the 2030s Will Robots Really Steal Our Jobs?

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Smart Data Collective

FEBRUARY 24, 2021

But the student in question was still able to create multiple articles for his master’s degree in business using the software. Tomorrow Sleep was launched in 2017 as a sleep system startup and ventured on to create online content in 2018. All he did was to create the outline and one sentence per paragraph.

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Mlearning.ai

JUNE 8, 2023

Hidden secret to empower semantic search This is the third article of building LLM-powered AI applications series. From the previous article , we know that in order to provide context to LLM, we need semantic search and complex query to find relevant context (traditional keyword search, full-text search won’t be enough).

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Google Research AI blog

FEBRUARY 28, 2023

For example, supporting equitable student persistence in computing research through our Computer Science Research Mentorship Program , where Googlers have mentored over one thousand students since 2018 — 86% of whom identify as part of a historically marginalized group.

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AssemblyAI

AUGUST 22, 2023

After processing an audio signal, an ASR system can use a language model to rank the probabilities of phonetically-equivalent phrases Starting in 2018, a new paradigm began to emerge. There are several reasons for this sort of behavior, and a discussion of them is outside of the purview of this article.

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Dataconomy

MAY 15, 2023

In this article, we will explain CarynAI and take a closer look at the rise of AI girlfriends. She started promoting herself on YouTube in 2018, and today she has over 750,000 subscribers. What is CarynAI? Meet people’s favorite AI girlfriend Caryn Marjorie, a popular Snapchatter, built an AI girlfriend called CarynAI.

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Towards AI

JULY 21, 2023

chiahsuan156/ODSQA This repository contains dataset for the IEEE SLT 2018 paper: ODSQA: OPEN-DOMAIN SPOKEN QUESTION ANSWERING DATASET… github.com Every Sunday we do a weekly round-up of NLP news and code drops from researchers around the world. If you enjoyed this article, help us out […] Paper: [link] Where is it?

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Heartbeat

JANUARY 29, 2024

At its core, Meta-Learning equips algorithms with the aptitude to quickly grasp new tasks and domains based on past experiences, paving the way for unparalleled problem-solving skills and generalization abilities. A Perspective View and Survey of Meta-Learning Kondu R. & Schulman, J.

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Dataconomy

MAY 8, 2023

In this article, we will explain some of the best AI drawing generators and try to answer related questions like “Is AI drawing art,” “What AI drawing app is everyone using,” “How AI drawing works,” and more. This makes images that look like dreams and are strange and psychedelic.

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How to Learn Machine Learning

JANUARY 10, 2023

According to fortunly , the demand for Blockchain has risen in recent years as we have obviously seen in the Crypto bull runs of 2018 and 2020. To summarize, Hopefully, after learning about the variety of the top prominent programming languages, you may be able to select one trustworthy programming language.

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ML Review

JUNE 4, 2018

However, in 2014 a number of high-profile AI labs began to release new approaches leveraging deep learning to improve performance. A large proportion of articles on image captioning tend to borrow from their excellent captioned image examples. 2018)[ 103 ] proposed a more natural method for attention, inspired by neuroscience.

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AWS Machine Learning Blog

MAY 2, 2023

JumpStart is a machine learning (ML) hub that can help you accelerate your ML journey. JumpStart provides many pre-trained language models called foundation models that can help you perform tasks such as article summarization, question answering, and conversation generation and image generation.

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