Data Science Dojo

MAY 24, 2024

For example, predictive maintenance in manufacturing uses machine learning to anticipate equipment failures before they occur, reducing downtime and saving costs. Deep Learning Deep learning is a subset of machine learning based on artificial neural networks, where the model learns to perform tasks directly from text, images, or sounds.

Deep Learning 195

Deep Learning Deep Learning Machine Learning Machine Learning 195

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

Smart Data Collective

JUNE 4, 2021

Deep Learning. Deep learning is a subset of machine learning that works similar to the biological brain. Use deep learning when the number of variables (columns) is high. Deep learning is used for speech recognition, board games AI, image recognition, and manipulation. Ensembling.

Data Science 133

Data Science Exploratory Data Analysis Machine Learning Machine Learning 133

ODSC - Open Data Science

FEBRUARY 17, 2023

Natural language processing (NLP) has been growing in awareness over the last few years, and with the popularity of ChatGPT and GPT-3 in 2022, NLP is now on the top of peoples’ minds when it comes to AI. Computer science, math, statistics, programming, and software development are all skills required in NLP projects.

Data Science 111

Data Science Deep Learning Deep Learning Natural Language Processing 111

Pickl AI

DECEMBER 26, 2024

Computer Hardware At the core of any Generative AI system lies the computer hardware, which provides the necessary computational power to process large datasets and execute complex algorithms. They learn patterns from extensive datasets before being fine-tuned for specific tasks or industries.

AI 52

AI AI Deep Learning Deep Learning 52

Analytics Vidhya

APRIL 6, 2023

It has been fueled by numerous factors, including advancements in computing technology and an increasing demand for automated systems. Artificial Intelligence (AI) has come a long way since its early days.

Artificial Intelligence 318

Artificial Intelligence Artificial Intelligence AI AI 318

Dataconomy

FEBRUARY 6, 2024

These companies are using AI and ML to improve existing processes, reduce risks, and predict business performance and industry trends. When it comes to the role of AI in information technology, machine learning, with its deep learning capabilities, is the best use case.

ML 121

ML ML Machine Learning Machine Learning 121

The MLOps Blog

MARCH 23, 2023

The size of large NLP models is increasing | Source Such large natural language processing models require significant computational power and memory, which is often the leading cause of high infrastructure costs. Cloud computing services are flexible and can scale according to your requirements.

Natural Language Processing 115

Natural Language Processing Cloud Computing AWS Deep Learning 115

How to Learn Machine Learning

MAY 14, 2023

When selecting projects, consider tackling problems in different domains, such as natural language processing, computer vision, or recommendation systems. In addition to deep learning, it’s beneficial to specialize in a specific area or technique within machine learning.

Machine Learning 52

Machine Learning Machine Learning Deep Learning Deep Learning 52

Applied Data Science

AUGUST 2, 2021

They bring deep expertise in machine learning , clustering , natural language processing , time series modelling , optimisation , hypothesis testing and deep learning to the team.

Data Science 130

Data Science Data Scientist ML ML 130

Smart Data Collective

JANUARY 13, 2022

They can accomplish much more complex functionalities than simple computer algorithms are capable of. For example, deep learning can be used to understand speech and also respond with speech. Search tools with Natural Language Processing (NLP) can bring the right solution with very little query effort.

Machine Learning 139

Machine Learning Machine Learning AI AI 139

Data Science Dojo

JULY 3, 2024

Machine Learning : Supervised and unsupervised learning algorithms, including regression, classification, clustering, and deep learning. Tools and frameworks like Scikit-Learn, TensorFlow, and Keras are often covered.

Data Science 150

Data Science Machine Learning Machine Learning Data Visualization 150

Heartbeat

DECEMBER 5, 2023

Third-generation Tensor Cores have accelerated AI tasks, leading to breakthroughs in image recognition, natural language processing, and speech recognition. The H100 pioneered AI computing with its capability of machine learning and deep learning workloads.

Natural Language Processing 52

Natural Language Processing Deep Learning Deep Learning Machine Learning 52

Pickl AI

SEPTEMBER 3, 2024

ReLU is widely used in Deep Learning due to its simplicity and effectiveness in mitigating the vanishing gradient problem. Tanh (Hyperbolic Tangent): This function maps input values to a range between -1 and 1, providing a smooth gradient for learning.

Natural Language Processing 52

Natural Language Processing Machine Learning Machine Learning Deep Learning 52

IBM Journey to AI blog

JULY 6, 2023

Python is the most common programming language used in machine learning. Machine learning and deep learning are both subsets of AI. Deep learning teaches computers to process data the way the human brain does. Deep learning algorithms are neural networks modeled after the human brain.

Machine Learning 70

Machine Learning Machine Learning Data Science Big Data 70

DataSeries

MARCH 1, 2023

Developed by OpenAI, ChatGPT is a natural language processing (NLP) model that can generate human-like conversations. ChatGPT is an AI-driven natural language processing (NLP) model that uses big data and generative pre-training (GPT) to learn how to generate natural language responses to user input.

Natural Language Processing 52

Natural Language Processing Python Artificial Intelligence Artificial Intelligence 52

Pickl AI

NOVEMBER 28, 2024

Understanding various Machine Learning algorithms is crucial for effective problem-solving. Familiarity with cloud computing tools supports scalable model deployment. Continuous learning is essential to keep pace with advancements in Machine Learning technologies.

Machine Learning 52

Machine Learning Machine Learning ML ML 52

Pickl AI

NOVEMBER 26, 2024

Summary: Recurrent Neural Networks (RNNs) are specialised neural networks designed for processing sequential data by maintaining memory of previous inputs. They excel in natural language processing, speech recognition, and time series forecasting applications. As the global neural network market expands—from $14.35

Natural Language Processing 52

Natural Language Processing Deep Learning Deep Learning Algorithm 52

The MLOps Blog

JUNE 27, 2023

Learn more The Best Tools, Libraries, Frameworks and Methodologies that ML Teams Actually Use – Things We Learned from 41 ML Startups [ROUNDUP] Key use cases and/or user journeys Identify the main business problems and the data scientist’s needs that you want to solve with ML, and choose a tool that can handle them effectively.

Machine Learning 134

Machine Learning Machine Learning ML ML 134

AWS Machine Learning Blog

OCTOBER 30, 2024

Sentence transformers are powerful deep learning models that convert sentences into high-quality, fixed-length embeddings, capturing their semantic meaning. These embeddings are useful for various natural language processing (NLP) tasks such as text classification, clustering, semantic search, and information retrieval.

Machine Learning 108

Machine Learning Machine Learning AWS Data Scientist 108

Dataconomy

MAY 2, 2023

What do machine learning engineers do: ML engineers design and develop machine learning models The responsibilities of a machine learning engineer entail developing, training, and maintaining machine learning systems, as well as performing statistical analyses to refine test results.

ML 110

ML ML Machine Learning Machine Learning 110

Snorkel AI

MAY 24, 2023

From generative modeling to automated product tagging, cloud computing, predictive analytics, and deep learning, the speakers present a diverse range of expertise. He leads corporate strategy for machine learning, natural language processing, information retrieval, and alternative data.

Machine Learning 52

Machine Learning Machine Learning Computer Science Computer Science 52

Snorkel AI

MAY 24, 2023

From generative modeling to automated product tagging, cloud computing, predictive analytics, and deep learning, the speakers present a diverse range of expertise. He leads corporate strategy for machine learning, natural language processing, information retrieval, and alternative data.

Machine Learning 52

Machine Learning Machine Learning Computer Science Computer Science 52

Pickl AI

SEPTEMBER 11, 2024

Unlike a bachelor’s program, which provides a broad overview, a master’s program delves deep into specific areas such as predictive analytics, natural language processing, or Artificial Intelligence. Hands-on Experience: Includes tools like Apache Spark, Tableau, TensorFlow, and Python for practical learning.

Data Science 52

Data Science Machine Learning Machine Learning Natural Language Processing 52

DrivenData Labs

DECEMBER 11, 2024

A number of breakthroughs are enabling this progress, and here are a few key ones: Compute and storage - The increased availability of cloud compute and storage has made it easier and cheaper to get the compute resources organizations need.

Data Science 147

Data Science Data Scientist Machine Learning Machine Learning 147

Pickl AI

SEPTEMBER 23, 2024

AI is making a difference in key areas, including automation, language processing, and robotics. Natural Language Processing: NLP helps machines understand and generate human language, enabling technologies like chatbots and translation. in Artificial Intelligence and Data Science.

Artificial Intelligence 52

Artificial Intelligence Artificial Intelligence Data Science Machine Learning 52

Pickl AI

SEPTEMBER 5, 2024

Microsoft Azure, often referred to as Azure, is a robust cloud computing platform developed by Microsoft. It offers a wide range of cloud services, including: Compute Power: Scalable virtual machines and container services for running applications. What is Azure?

Azure 52

Azure Data Scientist Data Science Machine Learning 52

DrivenData Labs

MARCH 30, 2023

Denis Loginov is a Principal Security Engineer at Broad Institute with the Data Sciences Platform with expertise in application security and cloud computing. Our current research focus is on the areas of reliable, secure, robust and fair machine learning, probabilistic and quantum programming, and machine learning for code.

Machine Learning 162

Machine Learning Machine Learning Data Science Algorithm 162

AWS Machine Learning Blog

AUGUST 14, 2023

In this post and accompanying notebook, we demonstrate how to deploy the BloomZ 176B foundation model using the SageMaker Python simplified SDK in Amazon SageMaker JumpStart as an endpoint and use it for various natural language processing (NLP) tasks. Question: When was NLP Cloud founded?

Natural Language Processing 98

Natural Language Processing AWS Machine Learning Machine Learning 98

AWS Machine Learning Blog

SEPTEMBER 21, 2023

They wanted to take advantage of machine learning (ML) techniques such as computer vision (CV) and natural language processing (NLP) to automate document processing pipelines. The process relies on manual annotations to train ML models, which are very costly.

AWS 131

AWS Machine Learning Machine Learning ML 131

Dataconomy

FEBRUARY 11, 2025

AI summers, such as those driven by advancements in deep learning, increased computational power, and big data analytics, have repeatedly revived interest and funding. Recent AI summers have been fueled by key innovations, including deep learning, increased computational power, and advancements in big data analytics.

AI 113

AI AI Big Data Analytics Big Data Analytics 113

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

AWS Machine Learning Blog

JANUARY 7, 2025

Traditional NLP pipelines and ML classification models Traditional natural language processing pipelines struggle with email complexity due to their reliance on rigid rules and poor handling of language variations, making them impractical for dynamic client communications.

AWS 111

AWS AI AI ML 111

Flipboard

APRIL 16, 2025

LLMs are large deep learning models that are pre-trained on vast amounts of data. Embeddings enable machine learning (ML) models to effectively process and understand relationships within complex data, leading to improved performance on various tasks like natural language processing and computer vision.

AWS 106

AWS Database AI AI 106