DrivenData Labs

MAY 18, 2023

My research focuses on differential privacy and explainable machine learning but extends to other areas where applying formal models brings new ideas to the table. My colleague Ryan McKenna had success in the 2018 Synthetic Data Challenge and was instrumental in getting me up to speed for this one.

Data Science 246

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ODSC - Open Data Science

SEPTEMBER 21, 2023

The majority of us who work in machine learning, analytics, and related disciplines do so for organizations with a variety of different structures and motives. The following is an extract from Andrew McMahon’s book , Machine Learning Engineering with Python, Second Edition.

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Dataconomy

MARCH 17, 2025

Machine learning algorithms: Utilizing recurrent neural networks and TensorFlow Extended, Duplex effectively handles various tasks with high accuracy and adaptability. Release and availability of Google Duplex Google Duplex made its debut at Google I/O 2018, where Sundar Pichai showcased its capabilities.

Natural Language Processing 91

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Smart Data Collective

FEBRUARY 24, 2021

You might have received a lengthy email from your coworker, and you could simply press on the ‘Got it’ response suggested by Google’s AI algorithm to compose your reply. However, this ever-evolving machine learning technology might surprise you in this regard. Machine Learning to Write your College Essays.

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Smart Data Collective

JUNE 24, 2023

Fortunately, new advances in machine learning technology can help mitigate many of these risks. Therefore, you will want to make sure that your cryptocurrency wallet or service is protected by machine learning technology. In 2018, researchers used data mining and machine learning to detect Ponzi schemes in Ethereum.

Machine Learning 98

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Towards AI

NOVEMBER 16, 2024

Keswani’s Algorithm introduces a novel approach to solving two-player non-convex min-max optimization problems, particularly in differentiable sequential games where the sequence of player actions is crucial. Keswani’s Algorithm: The algorithm essentially makes response function : maxy∈{R^m} f (.,

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ML @ CMU

JANUARY 2, 2025

In practice, our algorithm is off-policy and incorporates mechanisms such as two critic networks and target networks as in TD3 ( fujimoto et al., 2018 ) to enhance training (see Materials and Methods in Zhang et al.,

Deep Learning 336

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Flipboard

JANUARY 31, 2023

The app uses algorithmic predictions, which Kevin Systrom sees as ‘the future of social.’ The Instagram co-founders, who departed Facebook in 2018 amid tensions with their parent company, have formed a new venture to explore ideas for next-generation social … Kevin Systrom and Mike Krieger are back.

Algorithm 139

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NYU Center for Data Science

OCTOBER 16, 2024

The tweet linked to a paper from 2018, hinting at the foundational research behind these now-commercialized ideas. Back in 2018, recent CDS PhD grad Katrina Drozdov (née Evtimova), Cho, and their colleagues published a paper at ICLR called “ Emergent Communication in a Multi-Modal, Multi-Step Referential Game.”

Computer Science 95

Computer Science Computer Science Deep Learning Deep Learning 95

Data Science 101

JUNE 3, 2019

Playing Atari with Deep Reinforcement Learning (2013) – A bit older, but a classic in the reinforcement learning literature Model Evaluation, Model Selection, and Algorithm Selection in Machine Learning (2018) – title sums it up Borg, Omega, and Kubernetes (2016) – Kubernetes is widely used and this is one of the early papers Integer (..)

Data Science 96

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Dataconomy

OCTOBER 2, 2024

Kingma, is a prominent figure in the field of artificial intelligence and machine learning. cum laude in machine learning from the University of Amsterdam in 2017. His academic work, particularly in deep learning and generative models, has had a profound impact on the AI community. ” Who is Durk Kingma?

Machine Learning 103

Machine Learning Machine Learning Natural Language Processing Deep Learning 103

Heartbeat

FEBRUARY 6, 2023

How do Object Detection Algorithms Work? There are two main categories of object detection algorithms. Two-Stage Algorithms: Two-stage object detection algorithms consist of two different stages. Single-stage object detection algorithms do the whole process through a single neural network model.

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Algorithm Deep Learning Deep Learning ML 90

Smart Data Collective

JANUARY 14, 2021

A research project from Israel is helping solve the problem of overwhelming email messages by using big data algorithms to sort through email content more effectively. Mark Last, a professor with Ben Gurion University worked with his colleagues to develop some big data algorithms to summarize text more efficiently.

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Big Data Big Data Machine Learning Machine Learning 132

Flipboard

DECEMBER 4, 2024

In 2018, Google DeepMind's AlphaZero program taught itself the games of chess, shogi, and Go using machine learning and a special algorithm to determine the best moves to win a game within a defined grid.

Machine Learning 73

Machine Learning Machine Learning Algorithm Computer Science 73

Smart Data Collective

NOVEMBER 17, 2021

85,000 jobs disappeared from the retail sector in the first quarter of 2018, and about 30,000 retailers reported financial difficulties. from prior periods as of 2018. Here are some of the biggest ways that retailers are harnessing the power of machine learning and AI. In the U.K., Major AI Trends in Retail. Conclusion.

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How to Learn Machine Learning

OCTOBER 10, 2024

The quality of your training data in Machine Learning (ML) can make or break your entire project. This article explores real-world cases where poor-quality data led to model failures, and what we can learn from these experiences. Machine learning algorithms rely heavily on the data they are trained on.

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Machine Learning Machine Learning Data Quality Algorithm 52

Hacker News

JUNE 1, 2023

This is what I wrote in Click Here to Kill Everybody (2018): I am less worried about AI; I regard fear of AI more as a mirror of our own society than as a harbinger of the future. AI and intelligent robotics are the culmination of several precursor technologies, like machine learning algorithms, automation, and autonomy.

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AWS Machine Learning Blog

APRIL 7, 2025

This approach allows for greater flexibility and integration with existing AI and machine learning (AI/ML) workflows and pipelines. Chakravarthy Nagarajan is a Principal Solutions Architect specializing in machine learning, big data, and high performance computing. billion to a projected $574.78

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DagsHub

JUNE 3, 2024

In 2018, there were extensive news reports that an Uber self-driving car made an accident with a pedestrian in Tempe, Arizona. The pedestrian died, and investigators found that there was an issue with the machine learning (ML) model in the car, so it failed to identify the pedestrian beforehand. These are: 1.

Machine Learning 52

Machine Learning Machine Learning Decision Trees ML 52

Data Science 101

APRIL 26, 2019

Go Machine Learning Projects (2018) – this book uses gonum and gorgonia in the examples Machine Learning with Go (2017). Machine Learning with Go? In short, Golang is not widely used for exploratory data science, but rewriting your algorithms in Golang might be a good idea.

Data Science 111

Data Science Machine Learning Machine Learning Python 111

Alation

FEBRUARY 13, 2020

By matching landmarks on the human face or identifying patterns in speech rate, pitch range, intensity, and voice quality, AI is able to detect human emotions — some algorithms can even detect 10-different emotions. AI is not a fad, algorithmic decision-making is inevitable. Human Curation + Machine Learning.

Machine Learning 52

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AWS Machine Learning Blog

MARCH 8, 2023

MPII is using a machine learning (ML) bid optimization engine to inform upstream decision-making processes in power asset management and trading. SageMaker enables Marubeni to run ML and numerical optimization algorithms in a single environment. He has over 25 years of technology experience and has joined AWS in 2018.

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AWS Machine Learning Blog

OCTOBER 5, 2023

Before that, he worked on developing machine learning methods for fraud detection for Amazon Fraud Detector. He is passionate about applying machine learning, optimization, and generative AI techniques to various real-world problems. He focuses on developing scalable machine learning algorithms.

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Mlearning.ai

FEBRUARY 10, 2023

Techniques for reducing avoidable bias If you train your machine learning model and you see that your algorithm is suffering from high avoidable bias, you could the following techniques to reduce it. Summary Bias and variance are two main sources of error in machine learning. Machine learning yearning.

Machine Learning 52

Machine Learning Machine Learning Deep Learning Deep Learning 52

Dataconomy

OCTOBER 5, 2023

AI has made significant contributions to various aspects of our lives in the last five years ( Image credit ) How do AI technologies learn from the data we provide? AI technologies learn from the data we provide through a structured process known as training. Another form of machine learning algorithm is known as unsupervised learning.

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Dataconomy

SEPTEMBER 4, 2023

Predictive analytics: Predictive analytics leverages historical data and statistical algorithms to make predictions about future events or trends. Machine learning and AI analytics: Machine learning and AI analytics leverage advanced algorithms to automate the analysis of data, discover hidden patterns, and make predictions.

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ML @ CMU

DECEMBER 29, 2023

These factors introduce noise that can affect hyperparameter tuning algorithms and lead to suboptimal model selection. Hyperparameter tuning is critical to the success of cross-device federated learning applications. Three key factors differentiate FL from traditional centralized learning and distributed learning: Scale.

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Heartbeat

SEPTEMBER 13, 2023

This guide will buttress explainability in machine learning and AI systems. The explainability concept involves providing insights into the decisions and predictions made by artificial intelligence (AI) systems and machine learning models. What is Explainability?

Machine Learning 52

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Mlearning.ai

JUNE 8, 2023

Use algorithm to determine closeness/similarity of points. Instead, it’s the overall patterns of location and distance between vectors that machine learning takes advantage of. SentenceBERT: Currently, the leader among the pack, SentenceBERT was introduced in 2018 and immediately took the pole position for Sentence Embeddings.

Machine Learning 52

Machine Learning Machine Learning Clustering Database 52

Heartbeat

JANUARY 29, 2024

Photo by Brett Jordan on Unsplash In the ever-evolving landscape of artificial intelligence and machine learning, researchers and practitioners continuously seek to elevate the capabilities of intelligent systems. Among the myriad breakthroughs in this field, Meta-Learning is pushing the boundaries of machine learning.

Machine Learning 52

Machine Learning Machine Learning Natural Language Processing Algorithm 52

Mlearning.ai

APRIL 13, 2023

Photo by Robo Wunderkind on Unsplash In general , a data scientist should have a basic understanding of the following concepts related to kernels in machine learning: 1. Support Vector Machine Support Vector Machine ( SVM ) is a supervised learning algorithm used for classification and regression analysis.

Machine Learning 52

Machine Learning Machine Learning Data Scientist Support Vector Machines 52

Data Science Dojo

JUNE 26, 2023

In order to learn the nuances of language and to respond coherently and pertinently, deep learning algorithms are used along with a large amount of data. The BERT algorithm has been trained on 3.3 A Google AI language model called Bidirectional Encoder Representations from Transformers (BERT) was introduced in 2018.

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Mlearning.ai

APRIL 8, 2023

Charting the evolution of SOTA (State-of-the-art) techniques in NLP (Natural Language Processing) over the years, highlighting the key algorithms, influential figures, and groundbreaking papers that have shaped the field. NLP algorithms help computers understand, interpret, and generate natural language.

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Hacker News

MAY 6, 2023

I first ran across the Dartmouth group photo in 2018, when I was gathering material for Ray’s memorial website. Scientists interested in this latter approach were also represented at Dartmouth and later championed the rise of symbolic logic, using heuristic and algorithmic processes, which I’ll discuss in a bit.

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AWS Machine Learning Blog

FEBRUARY 29, 2024

is a startup dedicated to the mission of democratizing artificial intelligence technologies through algorithmic and software innovations that fundamentally change the economics of deep learning. He did his PhD in “Hashing Algorithms for Search and Information Retrieval” at Rice University. Founded in 2021, ThirdAI Corp.

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Dataconomy

MAY 29, 2023

Photoshop AI generative fill is a feature that uses machine learning and deep neural networks to analyze the image and synthesize new pixels that match the style and context of the original image. You don’t have to worry about that crowded travel photo you took in 2018. superjake100 We are bot ready for AI, yall.

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Flipboard

FEBRUARY 2, 2023

With advanced analytics derived from machine learning (ML), the NFL is creating new ways to quantify football, and to provide fans with the tools needed to increase their knowledge of the games within the game of football. There are around 3,000 and 4,000 plays from four NFL seasons (2018–2021) for punt and kickoff plays, respectively.

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