Data Science Dojo

DECEMBER 14, 2023

It could explain how these distributions are used in different machine learning algorithms and why understanding them is crucial for data scientists. 32 datasets to uplift your skills in data science Data Science Dojo has created an archive of 32 data sets for you to use to practice and improve your skills as a data scientist.

Natural Language Processing 195

Natural Language Processing Exploratory Data Analysis Machine Learning Machine Learning 195

Data Science Dojo

JULY 2, 2023

Over the past few years, a shift has shifted from Natural Language Processing (NLP) to the emergence of Large Language Models (LLMs). This evolution is fueled by the exponential expansion of available data and the successful implementation of the Transformer architecture.

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Data Science Dojo

JUNE 1, 2023

The course covers topics such as data wrangling, feature engineering, and model selection. Machine Learning for Natural Language Processing by Christopher Manning, Jurafsky and Schütze This is an advanced-level course that teaches you how to use machine learning for natural language processing tasks.

Machine Learning 195

Machine Learning Machine Learning Natural Language Processing Deep Learning 195

Data Science Dojo

OCTOBER 23, 2023

The Power of Embeddings with Vector Search Embeddings are a powerful tool for representing data in an easy-to-understand way for machine learning algorithms. Hugging Face + LangKit Hugging Face and LangKit are two popular open-source libraries for natural language processing (NLP).

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Database Data Analysis Data Analysis Artificial Intelligence 370

Smart Data Collective

DECEMBER 1, 2022

We should expect to analyze big data in the future as businesses are looking more closely to use it to remain competitive. This post outlines five current trends in big data for 2022 and beyond. Streaming analytics is a new trend in data analysis that has been gaining popularity in the past few years.

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Dataversity

DECEMBER 16, 2020

Deep learning is the basis for many complex computing tasks, including natural language processing (NLP), computer vision, one-to-one personalized marketing, and big data analysis. Click here to learn more about Gilad David Maayan.

Deep Learning 98

Deep Learning Deep Learning Natural Language Processing Big Data 98

Pickl AI

AUGUST 3, 2023

Introduction to Deep Learning Algorithms: Deep learning algorithms are a subset of machine learning techniques that are designed to automatically learn and represent data in multiple layers of abstraction. This process is known as training, and it relies on large amounts of labeled data.

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Deep Learning Deep Learning Machine Learning Machine Learning 52

Data Science Dojo

DECEMBER 14, 2023

It could explain how these distributions are used in different machine learning algorithms and why understanding them is crucial for data scientists. The data sets are categorized according to varying difficulty levels to be suitable for everyone. This blog will discuss the different natural language processing applications.

Data Science 195

Data Science Natural Language Processing AI AI 195

Pickl AI

AUGUST 1, 2023

Text mining is also known as text analytics or Natural Language Processing (NLP). It is the process of deriving valuable patterns, trends, and insights from unstructured textual data. Feature Extraction Methods Feature extraction involves identifying and selecting the most informative features from the text data.

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Data Analysis Data Analysis Python Support Vector Machines 52

Mlearning.ai

MAY 5, 2023

— Ilya Sutskever, chief scientist of OpenAI WE CAN CONNECT ON :| LINKEDIN | TWITTER | MEDIUM | SUBSTACK | In recent years, there has been a great deal of buzz surrounding large language models, or LLMs for short. In the 1980s and 1990s, the field of natural language processing (NLP) began to emerge as a distinct area of research within AI.

Natural Language Processing 98

Natural Language Processing Deep Learning Deep Learning Exploratory Data Analysis 98

Smart Data Collective

MARCH 27, 2023

Join the data revolution and secure a competitive edge for businesses vying for supremacy. Data Scientists and Analysts use various tools such as machine learning algorithms, statistical modeling, natural language processing (NLP), and predictive analytics to identify trends, uncover opportunities for improvement, and make better decisions.

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Data Analyst Data Science Data Scientist Natural Language Processing 92

Pickl AI

APRIL 19, 2024

Specialise in domains like machine learning or natural language processing to deepen expertise. Fundamental Concepts of AI Machine Learning: This branch of AI enables machines to learn from data and improve their performance over time without being explicitly programmed.

Natural Language Processing 52

Natural Language Processing AI AI Machine Learning 52

Dataconomy

JULY 18, 2023

By leveraging artificial intelligence algorithms and data analytics, manufacturers can streamline their quoting process, improve accuracy, and gain a competitive edge in the market. This information helps businesses estimate the resources required and adjust pricing accordingly in real-time.

AI 91

AI AI Algorithm Natural Language Processing 91

Data Science Dojo

MAY 16, 2023

Assists firms in identifying and refining their target market using data points and provides valuable insights. The algorithm helps find inactive customers through patterns and find reasons along with future predictions of people who might stop buying too. How can data science help in driving sales growth?

Data Science 195

Data Science Algorithm Natural Language Processing Data Mining 195

Dataconomy

MARCH 27, 2024

AI analyses vast amounts of data to find patterns and make predictions using that data. AI algorithms are able to flag suspicious transactions immediately by analyzing large datasets, identifying patterns, and detecting anomalies. Algorithms can detect patterns in machine sensor data that may indicate failure.

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Dataconomy

JUNE 13, 2023

In this era of information overload, utilizing the power of data and technology has become paramount to drive effective decision-making. Decision intelligence is an innovative approach that blends the realms of data analysis, artificial intelligence, and human judgment to empower businesses with actionable insights.

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Power BI Artificial Intelligence Artificial Intelligence Data Analysis 103

Pickl AI

JANUARY 29, 2024

Summary: In the tech landscape of 2024, the distinctions between Data Science and Machine Learning are pivotal. Data Science extracts insights, while Machine Learning focuses on self-learning algorithms. The collective strength of both forms the groundwork for AI and Data Science, propelling innovation. billion by 2029.

Data Science 52

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ODSC - Open Data Science

MAY 22, 2023

Training AI-Powered Algorithmic Trading with Python Dr. Yves J. Hilpisch | The AI Quant | CEO The Python Quants & The AI Machine, Adjunct Professor of Computational Finance This session will cover the essential Python topics and skills that will enable you to apply AI and Machine Learning (ML) to Algorithmic Trading.

Data Science 97

Data Science Machine Learning Machine Learning Python 97

Dataconomy

FEBRUARY 6, 2024

This popularity is primarily due to the spread of big data and advancements in algorithms. Going back from the times when AI was merely associated with futuristic visions to today’s reality, where ML algorithms seamlessly navigate our daily lives. These technologies have undergone a profound evolution. billion by 2032.

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ML ML AI AI 121

Chatbots Life

APRIL 16, 2024

Examples of Generative Models Generative models encompass various algorithms that capture patterns in data to generate realistic new examples. This is useful in natural language processing tasks. Training and Inference Process Training discriminative models involve feeding the model-labeled training data.

Natural Language Processing 59

Natural Language Processing Support Vector Machines Machine Learning Machine Learning 59

Data Science Dojo

NOVEMBER 10, 2023

However, becoming a skilled data scientist requires a lot of time and effort, as well as a deep understanding of statistics, programming, and data analysis techniques. Uses of generative AI for data scientists Generative AI can help data scientists with their projects in a number of ways.

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Dataconomy

APRIL 3, 2023

ML models are designed to learn from data and make predictions or decisions based on that data. Types of ML There are three main types of machine learning: Supervised learning: In supervised learning, the algorithm is trained on labeled data. The goal is to learn a policy that maximizes the cumulative reward over time.

Artificial Intelligence 70

Artificial Intelligence Artificial Intelligence Natural Language Processing AI 70

Dataconomy

APRIL 3, 2023

ML models are designed to learn from data and make predictions or decisions based on that data. Types of ML There are three main types of machine learning: Supervised learning: In supervised learning, the algorithm is trained on labeled data. The goal is to learn a policy that maximizes the cumulative reward over time.

Artificial Intelligence 70

Artificial Intelligence Artificial Intelligence Natural Language Processing AI 70

Data Science Connect

JULY 28, 2023

As data scientists, understanding this transformative synergy between AI and IoT is essential to unlock new possibilities in connectivity, data analysis, and decision-making. Intelligent Data Analytics With the inclusion of AI in IoT devices, data analytics capabilities become more sophisticated.

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Data Science Connect

JULY 28, 2023

In the ever-expanding landscape of artificial intelligence, language models have emerged as one of the most powerful tools for data scientists and enterprises. have revolutionized natural language processing (NLP) tasks, enabling machines to understand and generate human-like text.

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Dataconomy

APRIL 18, 2023

The basics of artificial intelligence include understanding the various subfields of AI, such as machine learning, natural language processing, computer vision, and robotics. Additionally, it is crucial to comprehend the fundamental concepts that underlie AI, including neural networks, algorithms, and data structures.

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Dataconomy

MAY 6, 2024

This makes them ideal for supporting complex machine learning and deep learning applications that require substantial processing power and parallel computing capabilities. B2B businesses in the machine learning sector are increasingly turning to advanced cloud GPU servers to handle large datasets and run intensive algorithms.

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Dataconomy

JULY 4, 2023

Examples of such tools include intelligent business process management, decision management, and business rules management AI and machine learning tools that enhance the capabilities of automation. ML algorithms enable systems to identify patterns, make predictions, and take autonomous actions.

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Dataconomy

JUNE 29, 2023

Python machine learning packages have emerged as the go-to choice for implementing and working with machine learning algorithms. These libraries, with their rich functionalities and comprehensive toolsets, have become the backbone of data science and machine learning practices. Why do you need Python machine learning packages?

Machine Learning 113

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ODSC - Open Data Science

FEBRUARY 27, 2023

Improved natural language processing : Natural language processing (NLP) is the ability of a computer to understand, interpret, and generate human language. In fact, many experts believe that we are on the cusp of some major breakthroughs in the field of artificial intelligence.

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Data Science Dojo

MAY 18, 2023

Getting Started with SQL Programming: Are you starting your journey in data science? Then you’re probably already familiar with SQL, Python, and R for data analysis and machine learning.

Data Science 195

Data Science AI AI SQL 195

Dataconomy

MAY 25, 2023

These devices collect and exchange data, creating a massive ecosystem that connects the physical and digital worlds. By leveraging advanced algorithms and machine learning techniques, IoT devices can analyze and interpret data in real-time, enabling them to make informed decisions and take autonomous actions.

Internet of Things 160

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ODSC - Open Data Science

AUGUST 31, 2023

The moment a cybercriminal drafts a strategy for avoiding counterfeit detectors, industry professionals reinforce them, making blockchain stronger to track and natural language processing more proficient at spotting textual inconsistencies. The relationship between AI and experts must remain strong.

Natural Language Processing 98

Natural Language Processing AI AI Data Scientist 98

Data Science Dojo

AUGUST 28, 2023

Development to production workflow LLMs Large Language Models (LLMs) represent a novel category of Natural Language Processing (NLP) models that have significantly surpassed previous benchmarks across a wide spectrum of tasks, including open question-answering, summarization, and the execution of nearly arbitrary instructions.

Exploratory Data Analysis 195

Exploratory Data Analysis Data Preparation Machine Learning Machine Learning 195

Towards AI

AUGUST 25, 2023

In ML, there are a variety of algorithms that can help solve problems. There is often confusion between the terms artificial intelligence and machine learning, which is discussed in The AI Process. There is often confusion between the terms artificial intelligence and machine learning, which is discussed in The AI Process.

Machine Learning 97

Machine Learning Machine Learning AI AI 97

Pickl AI

OCTOBER 25, 2023

It involves the use of algorithms, neural networks , and Machine Learning to enable machines to perform tasks that typically require human intelligence. Machine Learning algorithms enable systems to learn and improve from data without being explicitly programmed.

Big Data 52

Big Data Big Data Artificial Intelligence Artificial Intelligence 52

Towards AI

JUNE 27, 2023

For instance, today’s machine learning tools are pushing the boundaries of natural language processing, allowing AI to comprehend complex patterns and languages. Scikit Learn Scikit Learn is a comprehensive machine learning tool designed for data mining and large-scale unstructured data analysis.

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Machine Learning Machine Learning ML ML 95