KDnuggets

OCTOBER 14, 2019

Also: Activation maps for deep learning models in a few lines of code; The 4 Quadrants of Data Science Skills and 7 Principles for Creating a Viral Data Visualization; OpenAI Tried to Train AI Agents to Play Hide-And-Seek but Instead They Were Shocked by What They Learned; 10 Great Python Resources for Aspiring Data Scientists.

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Data Science Dojo

MARCH 31, 2023

Matul, who has experience working as an AI scientist at amazon, focused on dialogue machines and natural language understanding. Meanwhile, Francesca, a principal data scientist manager at Microsoft, leads teams of data scientists and ML scientists, working on internal problems at Microsoft.

Data Scientist 370

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Dataconomy

MARCH 17, 2025

PyTorch has emerged as one of the most prominent frameworks in the realm of machine learning and deep learning, captivating both researchers and developers alike. PyTorch is an open-source machine learning framework widely used for deep learning applications. What is PyTorch?

Natural Language Processing 91

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Data Science Dojo

APRIL 11, 2023

is an education technology company founded by Andrew Ng, a prominent figure in the world of AI and machine learning. The official Deep Learning AI YouTube channel offers video tutorials from the deep learning specialization on Coursera, covering a wide range of topics in AI and machine learning.

Data Science 195

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Data Science Dojo

OCTOBER 27, 2023

Data Science Dojo Large Language Models Bootcamp The Data Science Dojo Large Language Models Bootcamp is a 5-day in-person bootcamp that teaches you everything you need to know about large language models (LLMs) and their real-world applications. Who should attend?

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Data Science Dojo

FEBRUARY 23, 2023

These sessions cover a wide range of topics related to data science and AI, including data visualization, deep learning, and natural language processing. Register Now

Data Science 195

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Data Science Dojo

AUGUST 30, 2023

Statistical analysis and hypothesis testing Statistical methods provide powerful tools for understanding data. An Applied Data Scientist must have a solid understanding of statistics to interpret data correctly. Machine learning algorithms Machine learning forms the core of Applied Data Science.

Data Science 195

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Dataconomy

MARCH 19, 2025

They are essential for processing large amounts of data efficiently, particularly in deep learning applications. What are Tensor Processing Units (TPUs)? History of Tensor Processing Units The inception of TPUs can be traced back to 2015 when Google developed them for internal machine learning projects.

Machine Learning 91

Machine Learning Machine Learning Natural Language Processing Deep Learning 91

Pickl AI

JUNE 8, 2025

Trends in data science reflect technological advancements, evolving business needs, and new analytical methodologies that shape how data is collected, processed, and utilized. For data scientists and aspiring professionals, awareness of these trends guides skill development and career growth in a rapidly changing landscape.

Data Science 52

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Data Science Dojo

NOVEMBER 18, 2023

and other large language models (LLMs) have transformed natural language processing (NLP). Learning about LLMs is essential in today’s fast-changing technological landscape. But what if we could use deep learning to revolutionize search? Turbo, how to fine-tune GPT-3.5

Deep Learning 312

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Dataconomy

APRIL 3, 2025

t-SNE (t-distributed stochastic neighbor embedding) has become an essential tool in the realm of data analytics, standing out for its ability to unravel the complexities inherent in high-dimensional data.

Clustering 91

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ODSC - Open Data Science

APRIL 28, 2023

If a Natural Language Processing (NLP) system does not have that context, we’d expect it not to get the joke. In this post, I’ll be demonstrating two deep learning approaches to sentiment analysis. Deep learning refers to the use of neural network architectures, characterized by their multi-layer design (i.e.

Deep Learning 98

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Data Science Dojo

MAY 18, 2023

In case you were unable to attend the Future of Data and AI conference, we’ve compiled a list of all the tutorials and panel discussions for you to peruse and discover the innovative advancements presented at the Future of Data & AI conference. Check out our award-winning Data Science Bootcamp that can navigate your way.

Data Science 195

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Data Science Connect

JULY 24, 2023

The new breakthrough, known as Language Net, represents a significant leap forward in natural language understanding, opening up exciting possibilities for a wide range of applications. Data scientists and researchers are closely monitoring this advancement and its potential impact on the future of AI research.

Natural Language Processing 130

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Data Science Dojo

JANUARY 13, 2023

The conference features a wide range of topics within AI, including machine learning, natural language processing, computer vision, and robotics, as well as interdisciplinary areas such as AI and law, AI and education, and AI and the arts. PAW Climate and Deep Learning World.

Data Science 284

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Towards AI

DECEMBER 28, 2023

GenAI I serve as the Principal Data Scientist at a prominent healthcare firm, where I lead a small team dedicated to addressing patient needs. Over the past 11 years in the field of data science, I’ve witnessed significant transformations. CS6910/CS7015: Deep Learning Mitesh M. Khapra Homepage www.cse.iitm.ac.in

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AWS Machine Learning Blog

JANUARY 22, 2025

Converting free text to a structured query of event and time filters is a complex natural language processing (NLP) task that can be accomplished using FMs. Daniel Pienica is a Data Scientist at Cato Networks with a strong passion for large language models (LLMs) and machine learning (ML).

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Smart Data Collective

JUNE 4, 2021

Some of the applications of data science are driverless cars, gaming AI, movie recommendations, and shopping recommendations. Since the field covers such a vast array of services, data scientists can find a ton of great opportunities in their field. Data scientists use algorithms for creating data models.

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Dataconomy

FEBRUARY 19, 2025

Amazon AI is a comprehensive suite of artificial intelligence services provided by Amazon Web Services (AWS) that enables developers to build, train, and deploy machine learning and deep learning models. What is Amazon AI?

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AWS Machine Learning Blog

DECEMBER 12, 2024

The higher-level abstracted layer is designed for data scientists with limited AWS expertise, offering a simplified interface that hides complex infrastructure details. Data scientists can also seamlessly transition from local training to remote training and training on multiple nodes using the ModelTrainer.

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AWS Machine Learning Blog

NOVEMBER 29, 2024

22.03% The consistent improvements across different tasks highlight the robustness and effectiveness of Prompt Optimization in enhancing prompt performance for various natural language processing (NLP) tasks. Chris Pecora is a Generative AI Data Scientist at Amazon Web Services.

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Heartbeat

JULY 18, 2023

Source: Author Natural Language Processing (NLP) is a field of study focused on allowing computers to understand and process human language. There are many different NLP techniques and tools available, including the R programming language.

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Data Science Connect

JULY 29, 2023

A recent article on The Times of India sheds light on this groundbreaking initiative , highlighting how data scientists and law enforcement are teaming up to implement advanced facial recognition systems. Data scientists train these algorithms on large datasets to improve accuracy and reduce false positives.

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Data Science Connect

JULY 23, 2023

Data scientists and legal experts are closely monitoring the implications of this landmark shift in the intellectual property landscape. AI Inventor: A Novel Controversy The AI inventor in question is an advanced Generative AI system, equipped with sophisticated algorithms and deep learning capabilities.

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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.

Deep Learning 52

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Heartbeat

MARCH 22, 2023

Learn NLP data processing operations with NLTK, visualize data with Kangas , build a spam classifier, and track it with Comet Machine Learning Platform Photo by Stephen Phillips — Hostreviews.co.uk Many data we analyze as data scientists consist of a corpus of human-readable text.

Natural Language Processing 52

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Pickl AI

AUGUST 1, 2024

Summary : Deep Learning engineers specialise in designing, developing, and implementing neural networks to solve complex problems. Introduction Deep Learning engineers are specialised professionals who design, develop, and implement Deep Learning models and algorithms.

Deep Learning 52

Deep Learning Deep Learning Machine Learning Machine Learning 52

IBM Journey to AI blog

JULY 6, 2023

While artificial intelligence (AI), machine learning (ML), deep learning and neural networks are related technologies, the terms are often used interchangeably, which frequently leads to confusion about their differences. How do artificial intelligence, machine learning, deep learning and neural networks relate to each other?

Deep Learning 71

Deep Learning Deep Learning Machine Learning Machine Learning 71

ODSC - Open Data Science

JANUARY 26, 2023

Deep learning is one of the most crucial tools for analyzing massive amounts of data. However, there is such a prospect as too much information, as deep learning’s job is to find patterns and connections between data points to inform humanity’s questions and affirm assertions.

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Heartbeat

SEPTEMBER 20, 2023

Pixabay: by Activedia Image captioning combines natural language processing and computer vision to generate image textual descriptions automatically. Deep learning-based models, especially CNNs, have revolutionized feature extraction in image captioning.

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Heartbeat

OCTOBER 11, 2023

A key component of artificial intelligence is training algorithms to make predictions or judgments based on data. This process is known as machine learning or deep learning. Two of the most well-known subfields of AI are machine learning and deep learning. What is Deep Learning?

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Mlearning.ai

JULY 17, 2023

In today’s data-driven world, machine learning (ML) has become an indispensable tool for extracting valuable insights and making data-driven decisions. As a data scientist, staying ahead of the curve and continuously improving your skills is essential to tackle complex challenges in the field of ML.

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Heartbeat

MAY 2, 2023

Artificial intelligence has undergone a revolution thanks to deep learning. Deep learning allows machines to learn from vast amounts of data and carry out complex tasks that were previously only considered possible by humans (like translation between languages, recognizing objects etc.).

Deep Learning 52

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Heartbeat

AUGUST 29, 2023

Deep learning is a branch of machine learning that makes use of neural networks with numerous layers to discover intricate data patterns. Deep learning models use artificial neural networks to learn from data. It is a tremendous tool with the ability to completely alter numerous sectors.

Deep Learning 52

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Data Science Blog

JUNE 30, 2023

On own account, we from DATANOMIQ have created a web application that monitors data about job postings related to Data & AI from multiple sources (Indeed.com, Google Jobs, Stepstone.de

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AWS Machine Learning Blog

MARCH 21, 2025

The following is an example of how you can obtain metadata of the charts and graphs using simple natural language conversation with models. We provide the following request: sample_prompt = f""" You are a data scientist expert who has perfect vision and pay a lot of attention to details. We use the following graph.

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Heartbeat

JUNE 23, 2023

However, with the advent of deep learning, researchers have explored various neural network architectures to model and forecast time series data. In this post, we will look at deep learning approaches for time series analysis and how they might be used in real-world applications. Let’s dive in!

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