Data Science Dojo

SEPTEMBER 13, 2023

What are chatbots? AI chatbots are smart computer programs that can process and understand users’ requests and queries in voice and text. AI chatbots are widely used today from personal assistance to customer service and much more. AI chatbots are widely used today from personal assistance to customer service and much more.

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Flipboard

JUNE 20, 2023

Artificial intelligence (AI) is usually summarised as computers performing tasks that would otherwise require a human brain, such as playing chess, recognising faces, driving a car or reading a piece of text and picking out the important information. It underpins most of the advanced capabilities of AI systems.

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AWS Machine Learning Blog

OCTOBER 23, 2024

The landscape of enterprise application development is undergoing a seismic shift with the advent of generative AI. This intuitive platform enables the rapid development of AI-powered solutions such as conversational interfaces, document summarization tools, and content generation apps through a drag-and-drop interface.

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Towards AI

APRIL 23, 2024

Last Updated on April 25, 2024 by Editorial Team Author(s): Vincent Liu Originally published on Towards AI. Neural Style Transfer (NST) was born in 2015 [2], slightly later than GAN. It is one of the first algorithms to combine images based on deep learning. Join thousands of data leaders on the AI newsletter.

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Towards AI

JULY 8, 2024

Last Updated on July 8, 2024 by Editorial Team Author(s): Aditya Mohan Originally published on Towards AI. This is precisely where AI Accelerators come to the rescue! An overview of what lies ahead in this article… In this article, I will go over a small introduction to AI accelerators and how they differ from CPUs and GPUs.

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DagsHub

JULY 25, 2024

Source: Author Introduction Deep learning, a branch of machine learning inspired by biological neural networks, has become a key technique in artificial intelligence (AI) applications. Deep learning methods use multi-layer artificial neural networks to extract intricate patterns from large data sets.

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Dataconomy

OCTOBER 2, 2024

— Durk Kingma (@dpkingma) October 1, 2024 Kingma wrote, “Anthropic’s approach to AI development resonates significantly with my own beliefs; looking forward to contributing to Anthropic’s mission of developing powerful AI systems responsibly. He earned his Ph.D. Durk Kingma, also known as Diederik P.

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AWS Machine Learning Blog

APRIL 7, 2025

These models are designed for industry-leading performance in image and text understanding with support for 12 languages, enabling the creation of AI applications that bridge language barriers. With SageMaker AI, you can streamline the entire model deployment process.

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Flipboard

NOVEMBER 16, 2024

Raw images are processed and utilized as input data for a 2-D convolutional neural network (CNN) deep learning classifier, demonstrating an impressive 95% overall accuracy against new images. The glucose predictions done by CNN are compared with ISO 15197:2013/2015 gold standard norms.

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Towards AI

FEBRUARY 3, 2024

Author(s): Stavros Theocharis Originally published on Towards AI. PLoS ONE 10(7), e0130140 (2015) [2] Montavon, G., eds) Explainable AI: Interpreting, Explaining and Visualizing Deep Learning. link] Join thousands of data leaders on the AI newsletter. Published via Towards AI Lapuschkin, S.,

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Dataconomy

MAY 8, 2023

The constantly rising number of AI drawing generators is making it hard to find which one best fits your needs. If you are looking for an AI drawing generator list that explains the best of them, you have just found it and more information about AI art’s current state.

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Towards AI

AUGUST 11, 2023

Last Updated on August 16, 2023 by Editorial Team Author(s): Abid Ali Awan Originally published on Towards AI. Discover how tabular data space is being transformed by Kaggle competitions, the open-source community, and Generative AI. The synthetic datasets were created using a deep-learning generative network called CTGAN.[3]

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Towards AI

FEBRUARY 14, 2023

Generative AI involves the use of neural networks to create new content such as images, videos, or text. Generative AI is a fascinating field that has gained a lot of attention in recent years. It involves using machine learning algorithms to generate new data based on existing data. What is Generative AI?

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Towards AI

APRIL 19, 2024

Last Updated on April 21, 2024 by Editorial Team Author(s): Jennifer Wales Originally published on Towards AI. Get a closer view of the top generative AI companies making waves in 2024. They are soaring with career opportunities for certified AI professionals with the best AI certification programs.

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Dataconomy

NOVEMBER 20, 2023

Co-inventing AlexNet with Krizhevsky and Hinton, he laid the groundwork for modern deep learning. His fingerprints are also on the AlphaGo paper, showcasing his knack for staying ahead in the ever-evolving AI landscape. But, in 2015, he takes a leap of faith, leaving Google to co-found OpenAI.

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AWS Machine Learning Blog

OCTOBER 5, 2023

For more resources on using Trainium for distributed pre-training and fine-tuning your generative AI models using NeMo Megatron, refer to AWS Neuron Reference for NeMo Megatron. Before that, he worked on developing machine learning methods for fraud detection for Amazon Fraud Detector. Dr. Huan works on AI and Data Science.

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Towards AI

JULY 19, 2023

Last Updated on July 19, 2023 by Editorial Team Author(s): Chittal Patel Originally published on Towards AI. Deep learning algorithms can be applied to solving many challenging problems in image classification. 196–210, 2015. irregular illuminated conditions, shading, and blemishes. Yi, and J.-K. 567–577, 2013.

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Google Research AI blog

MARCH 7, 2023

words per image on average, which is more than 3x the density of TextOCR and 25x more dense than ICDAR-2015. Dataset Training split Validation split Testing split Words per image ICDAR-2015 1,000 0 500 4.4 These OCR products digitize and democratize the valuable information that is stored in paper or image-based sources (e.g.,

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Towards AI

FEBRUARY 27, 2024

Last Updated on February 27, 2024 by Editorial Team Author(s): IVAN ILIN Originally published on Towards AI. The whole machine learning industry since the early days was growing on open source solutions like scikit learn (2007) and then deep learning frameworks — TensorFlow (2015) and PyTorch (2016).

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Towards AI

AUGUST 11, 2023

Last Updated on August 12, 2023 by Editorial Team Author(s): Aditya Anil Originally published on Towards AI. The state of AI in 2014 was different from today. AI was picking up interests in the corporate world. Development in Deep Learning was at its golden state. What is it hinting to us?

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Towards AI

MAY 31, 2024

Last Updated on June 3, 2024 by Editorial Team Author(s): Suhaib Arshad Originally published on Towards AI. In deep learning, diffusion models have already replaced State-of-the-art generative frameworks like GANs or VAEs. In 2015 there was a paper published “Deep Unsupervised Learning using Nonequilibrium Thermodynamics” [1].

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AWS Machine Learning Blog

FEBRUARY 24, 2023

This dataset consists of human and machine annotated airborne images collected by the Civil Air Patrol in support of various disaster responses from 2015-2019. Amazon Rekognition makes it easy to add image and video analysis into our applications, using proven, highly scalable, deep learning technology. Sandeep Verma is a Sr.

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Pickl AI

FEBRUARY 14, 2023

Artificial Intelligence (AI) has emerged as one of the most efficient technologies for business organizations within the last few years. Accordingly, AI has become one of the leading technologies for Startups in India to cater to the end customers in the market. launched its meta framework on TensorFlow in 2015.

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Mlearning.ai

JUNE 16, 2023

The most common transfer learning recipe is suboptimal. The current practice of building AI applications in the Medical Imaging space often sticks to a suboptimal approach. However, current literature has repeatedly shown that this transfer learning approach has limits and is suboptimal for the medical domain. pre-training).

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Ines Montani

AUGUST 6, 2024

AI is making futurists of us all. Around 2015 when deep learning was widely adopted and conversational AI became more viable, the industry got very excited about chat bots. With the dizzying speed of new innovations, it’s clear that our lives and work are going to change. So what’s next?

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Towards AI

JULY 23, 2023

Last Updated on July 25, 2023 by Editorial Team Author(s): Abhijit Roy Originally published on Towards AI. Semi-Supervised Sequence Learning As we all know, supervised learning has a drawback, as it requires a huge labeled dataset to train. In 2015, Andrew M.

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Heartbeat

JULY 24, 2023

This article will cover briefly the architecture of the deep learning model used for the purpose. Koltun, “Multi-scale context aggregation by dilated convolutions,” arXiv preprint arXiv:1511.07122, 2015. [4] which was published on March 28, 2023.

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NYU Center for Data Science

SEPTEMBER 28, 2023

Linzen, for example, is interested in how human language works, which will never be solved simply by developing ever-more-sophisticated AI models. Cho’s work on building attention mechanisms within deep learning models has been seminal in the field. Looking Ahead The future of ML² is bright.

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Pickl AI

AUGUST 22, 2024

Introduction Deep Learning frameworks are crucial in developing sophisticated AI models, and driving industry innovations. By understanding their unique features and capabilities, you’ll make informed decisions for your Deep Learning applications.

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IBM Journey to AI blog

AUGUST 11, 2023

Machine learning (ML), a subset of artificial intelligence (AI), is an important piece of data-driven innovation. Machine learning engineers take massive datasets and use statistical methods to create algorithms that are trained to find patterns and uncover key insights in data mining projects.

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Snorkel AI

MAY 24, 2023

The Future of Data-centric AI virtual conference will bring together a star-studded lineup of expert speakers from across the machine learning, artificial intelligence, and data science field. DJ Patil , general partner at GreatPoint Ventures, will have a fireside chat with Snorkel AI CEO Alex Ratner.

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Snorkel AI

MAY 24, 2023

The Future of Data-centric AI virtual conference will bring together a star-studded lineup of expert speakers from across the machine learning, artificial intelligence, and data science field. DJ Patil , general partner at GreatPoint Ventures, will have a fireside chat with Snorkel AI CEO Alex Ratner.

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Pickl AI

APRIL 8, 2024

Summary: AI’s immense potential is undeniable, but its journey riddle with roadblocks. This blog explores 13 major AI blunders, highlighting issues like algorithmic bias, lack of transparency, and job displacement. 13 AI Mistakes That Are Worth Your Attention 1. 13 AI Mistakes That Are Worth Your Attention 1.

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ML Review

FEBRUARY 26, 2018

The most significant innovation in AI these recent years, smart chatbots, personal assistants, are only a glimpse of what the future holds. Launched in July 2015, AliMe is an IHCI-based shopping guide and assistant for e-commerce that overhauls traditional services, and improves the online user experience.

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AWS Machine Learning Blog

OCTOBER 9, 2023

He has 8 years of experience building out a variety of deep learning and other AI use cases and focuses on Personalization and Recommendation use cases with AWS. ACM Transactions on Interactive Intelligent Systems (TiiS) 5, 4, Article 19 (December 2015), 19 pages. References [1] Maxwell Harper and Joseph A.

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Pickl AI

JANUARY 23, 2023

It is mainly used for deep learning applications. PyTorch PyTorch is a popular, open-source, and lightweight machine learning and deep learning framework built on the Lua-based scientific computing framework for machine learning and deep learning algorithms. It also allows distributed training.

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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. In the past we’ve noted the huge effect of new datasets on research fields in AI. COCO enabled data-intensive deep neural networks to learn the mapping from images to sentences.

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