Pickl AI

JULY 25, 2023

Model Development Data Scientists develop sophisticated machine-learning models to derive valuable insights and predictions from the data. These models may include regression, classification, clustering, and more. Machine Learning: Supervised and unsupervised learning techniques, deep learning, etc.

Data Engineering 52

Data Engineering Data Engineer Data Engineering Data Engineering 52

IBM Journey to AI blog

JULY 6, 2023

These computer science terms are often used interchangeably, but what differences make each a unique technology? To keep up with the pace of consumer expectations, companies are relying more heavily on machine learning algorithms to make things easier. Machine learning is a subset of AI.

Deep Learning 63

Deep Learning Deep Learning Machine Learning Machine Learning 63

PyImageSearch

APRIL 3, 2023

Jump Right To The Downloads Section Deploying a Custom Image Classifier on an OAK-D Introduction As a deep learning engineer or practitioner, you may be working in a team building a product that requires you to train deep learning models on a specific data modality (e.g., computer vision) on a daily basis.

Deep Learning 64

Deep Learning Deep Learning AI AI 64

Mlearning.ai

JUNE 27, 2023

Hierarchical Clustering. Hierarchical Clustering: Since, we have already learnt “ K- Means” as a popular clustering algorithm. The other popular clustering algorithm is “Hierarchical clustering”. remember we have two types of “Hierarchical Clustering”. Divisive Hierarchical clustering. They are : 1.Agglomerative

Clustering 52

Clustering Algorithm Computer Science Computer Science 52

Dataconomy

MARCH 13, 2023

With advances in machine learning, deep learning, and natural language processing, the possibilities of what we can create with AI are limitless. Develop AI models using machine learning or deep learning algorithms. Machine learning and deep learning algorithms are commonly used in AI development.

Artificial Intelligence 98

Artificial Intelligence Artificial Intelligence Natural Language Processing Algorithm 98

NYU Center for Data Science

NOVEMBER 15, 2023

Pinheiro, Joshua Rackers, Joseph Kleinhenz, Michael Maser, *Omar Mahmood (PhD alumnus), Andrew Watkins, Stephen Ra, Vishnu Sresht, Saeed Saremi “A Logic for Expressing Log-Precision Transformers” : *William Merrill (PhD student), Ashish Sabharwal “A Neural Collapse Perspective on Feature Evolution in Graph Neural Networks” : Vignesh Kothapalli, Tom (..)

Data Science 82

Data Science Computer Science Computer Science Supervised Learning 82

Heartbeat

AUGUST 23, 2023

NLP is fundamentally an interdisciplinary field that blends linguistics, computer science, and artificial intelligence to provide robots with the capacity to comprehend and analyze human language. But exactly what is NLP , and how can it facilitate legal discovery? We pay our contributors, and we don’t sell ads.

Natural Language Processing 52

Natural Language Processing Algorithm Artificial Intelligence Artificial Intelligence 52

NYU Center for Data Science

JANUARY 25, 2024

Andrew Wilson (Associate Professor of Computer Science and Data Science) “ A Performance-Driven Benchmark for Feature Selection in Tabular Deep Learning ” by Valeriia Cherepanova, Roman Levin, Gowthami Somepalli, Jonas Geiping, C.

Computer Science 73

Computer Science Computer Science Data Science Supervised Learning 73

IBM Journey to AI blog

APRIL 18, 2024

Achieving these feats is accomplished through a combination of sophisticated algorithms, natural language processing (NLP) and computer science principles. Building an in-house team with AI, deep learning , machine learning (ML) and data science skills is a strategic move.

AI 97

AI AI Computer Science Computer Science 97

ODSC - Open Data Science

APRIL 21, 2023

With its applications in creativity, automation, business, advancements in NLP, and deep learning, the technology isn’t only opening new doors, but igniting the public imagination. Let’s take a look at what’s in store for you at ODSC East this May 9th-11th and what you’ll learn about generative AI when you attend.

AI 52

AI AI Azure Algorithm 52

Becoming Human

MARCH 16, 2023

Photo by NASA on Unsplash Hello and welcome to this post, in which I will study a relatively new field in deep learning involving graphs — a very important and widely used data structure. This post includes the fundamentals of graphs, combining graphs and deep learning, and an overview of Graph Neural Networks and their applications.

Clustering 87

Clustering Computer Science Computer Science Deep Learning 87

IBM Journey to AI blog

DECEMBER 20, 2023

What is machine learning? ML is a computer science, data science and artificial intelligence (AI) subset that enables systems to learn and improve from data without additional programming interventions. Here, we’ll discuss the five major types and their applications.

Machine Learning 82

Machine Learning Machine Learning Supervised Learning Clustering 82

PyImageSearch

JUNE 19, 2023

Figure 8: K-nearest neighbor algorithm (source: Towards Data Science ). Clustering Clustering is a class of algorithms that segregates the data into a set of definite clusters such that similar points lie in the same cluster and dissimilar points lie in different clusters. Several clustering algorithms (e.g.,

K-nearest Neighbors 56

K-nearest Neighbors Clustering Algorithm Deep Learning 56

AWS Machine Learning Blog

MAY 1, 2024

AWS Trainium instances for training workloads SageMaker ml.trn1 and ml.trn1n instances, powered by Trainium accelerators, are purpose-built for high-performance deep learning training and offer up to 50% cost-to-train savings over comparable training optimized Amazon Elastic Compute Cloud (Amazon EC2) instances.

AWS 89

AWS ML ML Clustering 89

Towards AI

APRIL 4, 2024

Machine learning (ML) has proven that it is here with us for the long haul, everyone who had their doubts by calling it a phase should by now realize how wrong they are, ML has being used in various sector’s of society such as medicine, geospatial data, finance, statistics and robotics.

K-nearest Neighbors 74

K-nearest Neighbors Machine Learning Machine Learning Decision Trees 74

AWS Machine Learning Blog

JUNE 7, 2023

Libraries such as DeepSpeed (an open-source deep learning optimization library for PyTorch) address some of these challenges, and can help accelerate model development and training. Training setup We provisioned a managed compute cluster comprised of 16 dl1.24xlarge instances using AWS Batch. Pre-training of a 1.5-billion-parameter

AWS 67

AWS Clustering Deep Learning Deep Learning 67

Flipboard

JULY 10, 2023

Figure 5: Architecture of Convolutional Autoencoder for Image Segmentation (source: Bandyopadhyay, “Autoencoders in Deep Learning: Tutorial & Use Cases [2023],” V7Labs , 2023 ). This can be helpful for visualization, data compression, and speeding up other machine learning algorithms. Join me in computer vision mastery.

Deep Learning 110

Deep Learning Deep Learning Machine Learning Machine Learning 110

PyImageSearch

OCTOBER 2, 2023

Jump Right To The Downloads Section A Deep Dive into Variational Autoencoder with PyTorch Introduction Deep learning has achieved remarkable success in supervised tasks, especially in image recognition. Similar class labels tend to form clusters, as observed with the Convolutional Autoencoder. That’s not the case.

Deep Learning 120

Deep Learning Deep Learning Clustering Computer Science 120

PyImageSearch

JULY 3, 2023

These features can be simple metadata or model-based features (extracted from a deep learning model), representing how good that video is for a member. Users are grouped into small clusters based on their viewing history to obtain context-only features. Or requires a degree in computer science? That’s not the case.

Deep Learning 52

Deep Learning Deep Learning Algorithm Machine Learning 52

PyImageSearch

OCTOBER 23, 2023

This kind of structured setup is common in deep learning projects to organize outputs and model checkpoints systematically. The chosen optimizer is the Adam optimizer, a popular optimization algorithm in deep learning. The optimizer requires the model’s parameters ( model.parameters() ) and a learning rate ( config.LR

Deep Learning 67

Deep Learning Deep Learning Computer Science Computer Science 67

Flipboard

AUGUST 17, 2023

Here we use RedshiftDatasetDefinition to retrieve the dataset from the Redshift cluster. In the processing job API, provide this path to the parameter of submit_jars to the node of the Spark cluster that the processing job creates. We attached the IAM role to the Redshift cluster that we created earlier.

ML 93

ML ML AWS Data Warehouse 93

Mlearning.ai

MAY 23, 2023

Machine learning has become a transformative technology across various fields, revolutionizing complex problem-solving. With the advancement of technology, machine learning, and computer vision techniques can be used to develop automated solutions for leaf disease detection. Working Video of our App [link] 20.

Machine Learning 52

Machine Learning Machine Learning K-nearest Neighbors Python 52

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.

ML 72

ML ML Deep Learning Deep Learning 72

Mlearning.ai

JUNE 25, 2023

Overview of Quantum Error Mitigation in NISQ through QML This article is part of our research under the guidance of Professor N.Geethanjali, Department of Computer Science & Technology, Sri Krishnadevaraya University, Andhra Pradesh State , INDIA. References Near-Term Quantum Computing Techniques [link] 2.

Algorithm 52

Algorithm Machine Learning Machine Learning Deep Learning 52

DrivenData Labs

DECEMBER 7, 2023

Solvers submitted a wide range of methodologies to this end, including using open-source and third party LLMs (GPT, LLaMA), clustering (DBSCAN, K-Means), dimensionality reduction (PCA), topic modeling (LDA, BERT), sentence transformers, semantic search, named entity recognition, and more. and DistilBERT.

Natural Language Processing 130

Natural Language Processing Clustering Data Science Data Analysis 130

AWS Machine Learning Blog

FEBRUARY 10, 2023

As an example, in the following figure, we separate Cover 3 Zone (green cluster on the left) and Cover 1 Man (blue cluster in the middle). We design an algorithm that automatically identifies the ambiguity between these two classes as the overlapping region of the clusters. Outside of work, he enjoys soccer and video games.

ML 66

ML ML Machine Learning Machine Learning 66

Snorkel AI

MARCH 31, 2023

I lead the NLP product line at SambaNova, and prior to that, I held engineering and product roles across the full AI stack—from chip design to software to deep learning model development and deployment. Deep learning became the new focus, first led by the advance in computer vision, then followed by natural language processing.

Deep Learning 52

Deep Learning Deep Learning AI AI 52

Snorkel AI

MARCH 31, 2023

I lead the NLP product line at SambaNova, and prior to that, I held engineering and product roles across the full AI stack—from chip design to software to deep learning model development and deployment. Deep learning became the new focus, first led by the advance in computer vision, then followed by natural language processing.

Deep Learning 52

Deep Learning Deep Learning AI AI 52

AWS Machine Learning Blog

APRIL 18, 2023

One of the major challenges in training and deploying LLMs with billions of parameters is their size, which can make it difficult to fit them into single GPUs, the hardware commonly used for deep learning. He focuses on developing scalable machine learning algorithms. Outside of work, he enjoys running and hiking.

ML 66

ML ML Deep Learning Deep Learning 66

O'Reilly Media

OCTOBER 19, 2021

Not only is data larger, but models—deep learning models in particular—are much larger than before. Prior to the cloud, setting up and operating a cluster that can handle workloads like this would have been a major technical challenge. To plug this gap, frameworks like Metaflow or MLFlow provide a custom solution for versioning.

ML 138

ML ML Data Scientist AWS 138

AWS Machine Learning Blog

MAY 24, 2023

Completion.execute( sm_endpoint=endpoint_name, prompt="Explain deep learning algorithms to 8th graders", numResults=1, maxTokens=100, temperature=0.01 #subject to reduce “hallucination” by using common words. As an alternative, you can use FAISS , an open-source vector clustering solution for storing vectors.

AI 73

AI AI AWS ML 73

AWS Machine Learning Blog

APRIL 18, 2023

One of the major challenges in training and deploying LLMs with billions of parameters is their size, which can make it difficult to fit them into single GPUs, the hardware commonly used for deep learning. He focuses on developing scalable machine learning algorithms. Outside of work, he enjoys running and hiking.

ML 52

ML ML Deep Learning Deep Learning 52

AWS Machine Learning Blog

JANUARY 13, 2023

FedML supports several out-of-the-box deep learning algorithms for various data types, such as tabular, text, image, graphs, and Internet of Things (IoT) data. His research focuses on distributed/federated machine learning algorithms, systems, and applications. Define the model. Chaoyang He is Co-founder and CTO of FedML, Inc.,

AWS 70

AWS Analytics Analytics Machine Learning 70

The MLOps Blog

OCTOBER 3, 2023

Mikiko Bazeley: Most people are really surprised to hear that my background in college was not computer science. With the full-stack deep learning course, there were some TAs there who were absolutely amazing. I would need to have the infrastructure to perform computations. I really enjoyed it. How was my code?”

ML 52

ML ML Data Scientist Machine Learning 52

DrivenData Labs

DECEMBER 10, 2023

or GPT-4 arXiv, OpenAlex, CrossRef, NTRS lgarma Topic clustering and visualization, paper recommendation, saved research collections, keyword extraction GPT-3.5 Concurrently, he is a neuroscience student at Ben Gurion University and a research assistant in a computational neuroscience lab. bge-small-en-v1.5

AI 147

AI AI Natural Language Processing Artificial Intelligence 147

AWS Machine Learning Blog

NOVEMBER 1, 2023

Utilizing the latest Hugging Face LLM modules on Amazon SageMaker, AWS customers can now tap into the power of SageMaker deep learning containers (DLCs). She is a technologist with a PhD in Computer Science, a master’s degree in Education Psychology, and years of experience in data science and independent consulting in AI/ML.

AWS 94

AWS Clustering Deep Learning Deep Learning 94

PyImageSearch

MAY 1, 2023

Redmon and Farhadi (2017) published YOLOv2 at the CVPR Conference and improved the original model by incorporating batch normalization, anchor boxes, and dimension clusters. Do you think learning computer vision and deep learning has to be time-consuming, overwhelming, and complicated? Yes, you read it right!

Deep Learning 107

Deep Learning Deep Learning Python Algorithm 107