Data Science Dojo

AUGUST 19, 2024

Industry Adoption: Widespread Implementation: AI and data science are being adopted across various industries, including healthcare, finance, retail, and manufacturing, driving increased demand for skilled professionals. This is used for tasks like clustering, dimensionality reduction, and anomaly detection.

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Data Science Dojo

JULY 3, 2024

Data science bootcamps are intensive short-term educational programs designed to equip individuals with the skills needed to enter or advance in the field of data science. They cover a wide range of topics, ranging from Python, R, and statistics to machine learning and data visualization.

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Data Science Dojo

JUNE 10, 2024

Data scientists are continuously advancing with AI tools and technologies to enhance their capabilities and drive innovation in 2024. The integration of AI into data science has revolutionized the way data is analyzed, interpreted, and utilized. – Example: Data scientists can employ H2O.ai

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Applied Data Science

AUGUST 2, 2021

This post is a bitesize walk-through of the 2021 Executive Guide to Data Science and AI  — a white paper packed with up-to-date advice for any CIO or CDO looking to deliver real value through data. Team Building the right data science team is complex. Download the free, unabridged version here.

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Data Science Blog

MAY 22, 2023

der k-Nächste-Nachbarn -Prädiktionsalgorithmus (Regression/Klassifikation) oder K-Means-Clustering. Die Texte müssen in diese transformiert werden, eventuell auch nach diesen in Cluster eingeteilt und für verschiedene Trainingsszenarien separiert werden. appeared first on Data Science Blog.

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DrivenData Labs

DECEMBER 11, 2024

Looking back ¶ When we started DrivenData in 2014, the application of data science for social good was in its infancy. There was rapidly growing demand for data science skills at companies like Netflix and Amazon. Weve run 75+ data science competitions awarding more than $4.7

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Data Science Blog

JUNE 30, 2023

The data is obtained from the Internet via APIs and web scraping, and the job titles and the skills listed in them are identified and extracted from them using Natural Language Processing (NLP) or more specific from Named-Entity Recognition (NER).

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Pickl AI

MARCH 27, 2023

Well, it’s Natural Language Processing which equips the machines to work like a human. But there is much more to NLP, and in this blog, we are going to dig deeper into the key aspects of NLP, the benefits of NLP and Natural Language Processing examples. What is NLP? However, the road is not so smooth.

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Flipboard

DECEMBER 3, 2024

As a global leader in agriculture, Syngenta has led the charge in using data science and machine learning (ML) to elevate customer experiences with an unwavering commitment to innovation. His primary focus lies in using the full potential of data, algorithms, and cloud technologies to drive innovation and efficiency.

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Data Science Dojo

JUNE 20, 2023

BERT (Bidirectional Encoder Representations from Transformers) BERT is a revolutionary transformer-based model that underwent extensive pre-training on vast amounts of text data. Its prowess lies in natural language processing (NLP) tasks like sentiment analysis, question-answering, and text classification.

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Data Science Dojo

AUGUST 16, 2024

Imagine asking a question in plain English and instantly getting a detailed report or a visual representation of your data—this is what GenAI can do. It’s not just for tech experts anymore; GenAI democratizes data science, allowing anyone to extract insights from data easily.

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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. The chart below shows 20 in-demand skills that encompass both NLP fundamentals and broader data science expertise.

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Data Science Dojo

MAY 10, 2024

Hence, acting as a translator it converts human language into a machine-readable form. These embeddings when particularly used for natural language processing (NLP) tasks are also referred to as LLM embeddings. Their impact on ML tasks has made them a cornerstone of AI advancements.

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Data Science Dojo

AUGUST 3, 2023

Faiss is a library for efficient similarity search and clustering of dense vectors. They are used in a variety of AI applications, such as image search, natural language processing, and recommender systems. Vector embeddings are a powerful tool for representing and manipulating data.

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Data Science Dojo

JANUARY 30, 2024

Exploring Disease Mechanisms : Vector databases facilitate the identification of patient clusters that share similar disease progression patterns. Here are a few key components of the discussed process described below: Feature engineering : Transforming raw clinical data into meaningful numerical representations suitable for vector space.

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AWS Machine Learning Blog

APRIL 4, 2025

To achieve this, Lumi developed a classification model based on BERT (Bidirectional Encoder Representations from Transformers) , a state-of-the-art natural language processing (NLP) technique. They fine-tuned this model using their proprietary dataset and in-house data science expertise. Follow her on LinkedIn.

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Data Science Dojo

AUGUST 18, 2023

Transformers are a type of neural network that are well-suited for natural language processing tasks. They are able to learn long-range dependencies between words, which is essential for understanding the nuances of human language. They are typically trained on clusters of computers or even on cloud computing platforms.

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Pickl AI

MAY 10, 2023

Being an important component of Data Science, the use of statistical methods are crucial in training algorithms in order to make classification. Certainly, these predictions and classification help in uncovering valuable insights in data mining projects. It can also be used for determining the optimal number of clusters.

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Data Science Dojo

JANUARY 31, 2024

It is an AI framework and a type of natural language processing (NLP) model that enables the retrieval of information from an external knowledge base. Facebook AI similarity search (FAISS) FAISS is used for similarity search and clustering dense vectors. Let’s take a deeper look into understanding RAG.

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Mlearning.ai

APRIL 10, 2023

How this machine learning model has become a sustainable and reliable solution for edge devices in an industrial network An Introduction Clustering (cluster analysis - CA) and classification are two important tasks that occur in our daily lives. 3 feature visual representation of a K-means Algorithm.

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Data Science Dojo

JULY 17, 2023

TensorFlow First on the AI tool list, we have TensorFlow which is an open-source software library for numerical computation using data flow graphs. It is used for machine learning, natural language processing, and computer vision tasks. For example, Scikit-learn was used by Spotify to improve its recommendation engine.

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Dataconomy

SEPTEMBER 22, 2023

There are several techniques used in intelligent data classification, including: Machine learning : Machine learning algorithms can be trained on large datasets to recognize patterns and categories within the data. Clustering algorithms work by assigning data points to clusters based on their similarity.

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IBM Data Science in Practice

MARCH 13, 2023

With IBM Watson NLP, IBM introduced a common library for natural language processing, document understanding, translation, and trust. This tutorial walks you through the steps to serve pretrained Watson NLP models using Knative Serving in a Red Hat OpenShift cluster. For more information see [link].

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Mlearning.ai

MAY 23, 2023

While specific requirements may vary depending on the organization and the role, here are the key skills and educational background that are required for entry-level data scientists — Skillset Mathematical and Statistical Foundation Data science heavily relies on mathematical and statistical concepts.

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Pickl AI

NOVEMBER 5, 2024

Summary: Data Science and AI are transforming the future by enabling smarter decision-making, automating processes, and uncovering valuable insights from vast datasets. Bureau of Labor Statistics predicts that employment for Data Scientists will grow by 36% from 2021 to 2031 , making it one of the fastest-growing professions.

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Pickl AI

JULY 10, 2023

What is R in Data Science? R is an open-source programming language that you can use for free and is compatible with different operating systems and platforms. As a programming language it provides objects, operators and functions allowing you to explore, model and visualise data. How is R Used in Data Science?

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Data Science Dojo

MAY 10, 2024

Hence, acting as a translator it converts human language into a machine-readable form. These embeddings when particularly used for natural language processing (NLP) tasks are also referred to as LLM embeddings. Their impact on ML tasks has made them a cornerstone of AI advancements.

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Pickl AI

MARCH 7, 2024

Summary: In 2024, mastering essential Data Science tools will be pivotal for career growth and problem-solving prowess. offer the best online Data Science courses tailored for beginners and professionals, focusing on practical learning and industry relevance. Why learn tools of Data Science? Join Pickl.AI

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AWS Machine Learning Blog

DECEMBER 29, 2022

Note: If you already have an RStudio domain and Amazon Redshift cluster you can skip this step. Amazon Redshift Serverless cluster. Just load your data and start querying. There is no need to set up and manage clusters. Loading data in Amazon Redshift Serverless. 1 Public subnet. 1 NAT gateway. Internet gateway.

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Pickl AI

SEPTEMBER 23, 2024

Summary: The blog explores the synergy between Artificial Intelligence (AI) and Data Science, highlighting their complementary roles in Data Analysis and intelligent decision-making. Introduction Artificial Intelligence (AI) and Data Science are revolutionising how we analyse data, make decisions, and solve complex problems.

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Pickl AI

SEPTEMBER 12, 2024

Summary : This article equips Data Analysts with a solid foundation of key Data Science terms, from A to Z. Introduction In the rapidly evolving field of Data Science, understanding key terminology is crucial for Data Analysts to communicate effectively, collaborate effectively, and drive data-driven projects.

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Pickl AI

MAY 31, 2023

With the expanding field of Data Science, the need for efficient and skilled professionals is increasing. You need to be highly proficient in programming languages to help businesses solve problems. Python is one of the widely used programming languages in the world having its own significance and benefits.

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IBM Journey to AI blog

DECEMBER 20, 2023

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. K-means clustering is commonly used for market segmentation, document clustering, image segmentation and image compression.

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Pickl AI

JULY 18, 2023

Data Science helps businesses uncover valuable insights and make informed decisions. But for it to be functional, programming languages play an integral role. Programming for Data Science enables Data Scientists to analyze vast amounts of data and extract meaningful information.

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NYU Center for Data Science

JUNE 30, 2023

To learn more about how NYUTron was developed along with the limitations and possibilities of AI support tools for healthcare providers, CDS spoke with Lavender Jiang , PhD student at the NYU Center for Data Science and lead author of the study. Read our Q&A with Lavender below! The resources NYU has are unique and valuable.

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AWS Machine Learning Blog

SEPTEMBER 3, 2024

By using the Livy REST APIs , SageMaker Studio users can also extend their interactive analytics workflows beyond just notebook-based scenarios, enabling a more comprehensive and streamlined data science experience within the Amazon SageMaker ecosystem. This same interface is also used for provisioning EMR clusters.

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AWS Machine Learning Blog

JUNE 11, 2024

In our test environment, we observed 20% throughput improvement and 30% latency reduction across multiple natural language processing models. So far, we have migrated PyTorch and TensorFlow based Distil RoBerta-base, spaCy clustering, prophet, and xlmr models to Graviton3-based c7g instances.

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