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). Transformers, a type of Deep Learning model, have played a crucial role in the rise of LLMs.

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PyImageSearch

JANUARY 30, 2023

This last blog of the series will cover the benefits, applications, challenges, and tradeoffs of using deep learning in the education sector. To learn about Computer Vision and Deep Learning for Education, just keep reading. As soon as the system adapts to human wants, it automates the learning process accordingly.

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Data Science Blog

MAY 22, 2023

Vektor-Datenbanken sind ein weiterer Typ von Datenbank, die unter Einsatz von AI (Deep Learning, n-grams, …) Wissen in Vektoren übersetzen und damit vergleichbarer und wieder auffindbarer machen. Diese Funktion der Datenbank spielt seinen Vorteil insbesondere bei vielen Dimensionen aus, wie sie Text- und Bild-Daten haben.

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Data Science Dojo

FEBRUARY 23, 2023

This Data Science boot camp is an intensive five-day program that provides hands-on training in data science, machine learning, and predictive analytics. Participants will learn how to build and deploy predictive models using Python, R, and other tools.

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Dataconomy

SEPTEMBER 25, 2024

AI integration in real-time data processing Artificial intelligence enhances real-time data processing through better comprehension with the help of advanced machine learning algorithms and analytics to act on that information. Natural language processing AI is the enabler of real-time analytics of texts and speeches.

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Dataconomy

JANUARY 24, 2024

The company is renowned for its deep understanding of machine learning and natural language processing technologies, providing practical AI solutions tailored to businesses’ unique needs. Their AI services encompass machine learning, predictive analytics, chatbots, and cognitive computing.

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Dataconomy

APRIL 27, 2023

An AI computer, also known as an artificial intelligence computer, is a computer system that is specifically designed to perform tasks that would typically require human intelligence, such as reasoning, problem-solving, and learning. They can also switch between different tasks and learn from new data.

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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.

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Pickl AI

JULY 12, 2024

Summary: This guide explores Artificial Intelligence Using Python, from essential libraries like NumPy and Pandas to advanced techniques in machine learning and deep learning. TensorFlow and Keras: TensorFlow is an open-source platform for machine learning.

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ODSC - Open Data Science

MARCH 11, 2024

NLP and LLMs The NLP and LLMs track will give you the opportunity to learn firsthand from core practitioners and contributors about the latest trends in data science languages and tools, such as pre-trained models, with use cases focusing on deep learning, speech-to-text, and semantic search.

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Data Science Blog

FEBRUARY 23, 2023

1, Data is the new oil, but labeled data might be closer to it Even though we have been in the 3rd AI boom and machine learning is showing concrete effectiveness at a commercial level, after the first two AI booms we are facing a problem: lack of labeled data or data themselves.

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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. However, the rapid evolution of these machine learning tools also presents a challenge for developers.

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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.

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Dataconomy

MARCH 27, 2023

Some of the ways in which ML can be used in process automation include the following: Predictive analytics:  ML algorithms can be used to predict future outcomes based on historical data, enabling organizations to make better decisions. Technology: Includes a range of technologies, including ML and deep learning.

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Pickl AI

SEPTEMBER 17, 2024

Summary : AI is transforming the cybersecurity landscape by enabling advanced threat detection, automating security processes, and adapting to new threats. It leverages Machine Learning, natural language processing, and predictive analytics to identify malicious activities, streamline incident response, and optimise security measures.

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IBM Journey to AI blog

JULY 11, 2023

AI technologies like natural language processing (NLP), predictive analytics and speech recognition can lead to healthcare providers having more effective communication with patients, which can lead to better patient experience, care and outcomes.

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Pickl AI

SEPTEMBER 30, 2024

Enhancing Decision-Making with Data-Driven Insights Machine Learning empowers businesses to make smarter decisions by analysing vast amounts of data and uncovering hidden patterns. Companies can leverage predictive analytics to forecast market trends, optimise pricing strategies, and identify potential risks.

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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. Continuous Evaluation: Frequent assessments help professionals stay on track with their studies.

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Heartbeat

OCTOBER 23, 2023

By utilizing techniques like computer vision and deep learning, they can detect abnormalities, assist in disease diagnosis, and provide quantitative measurements. For instance, machine learning algorithms have proven more accurate and efficient in disease diagnosis than manual interpretation of medical images.

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Dataconomy

MARCH 27, 2023

Some of the ways in which ML can be used in process automation include the following: Predictive analytics:  ML algorithms can be used to predict future outcomes based on historical data, enabling organizations to make better decisions. Technology: Includes a range of technologies, including ML and deep learning.

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Pickl AI

SEPTEMBER 23, 2024

Healthcare Data Science is revolutionising healthcare through predictive analytics, personalised medicine, and disease detection. For example, it helps predict patient outcomes, optimise hospital operations, and discover new drugs. AI is making a difference in key areas, including automation, language processing, and robotics.

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Dataconomy

MAY 25, 2023

AI algorithms can uncover hidden correlations within IoT data, enabling predictive analytics and proactive actions. Here are some ways AI enhances IoT devices: Advanced data analysis AI algorithms can process and analyze vast volumes of IoT-generated data. Deep learning, in combination with IoT, unlocks various possibilities.

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IBM Journey to AI blog

DECEMBER 20, 2023

And retailers frequently leverage data from chatbots and virtual assistants, in concert with ML and natural language processing (NLP) technology, to automate users’ shopping experiences. Regression algorithms —predict output values by identifying linear relationships between real or continuous values (e.g.,

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Pickl AI

JULY 20, 2023

Root cause analysis is a typical diagnostic analytics task. 3. Predictive Analytics Projects: Predictive analytics involves using historical data to predict future events or outcomes. These projects predict what is likely to happen and suggest the best course of action to achieve desired results.

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IBM Journey to AI blog

JULY 6, 2023

One ride-hailing transportation company uses big data analytics to predict supply and demand, so they can have drivers at the most popular locations in real time. An e-commerce conglomeration uses predictive analytics in its recommendation engine. Python is the most common programming language used in machine learning.

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Pickl AI

NOVEMBER 18, 2024

Common Applications of Machine Learning Machine Learning has numerous applications across industries. Predictive analytics uses historical data to forecast future trends, such as stock market movements or customer churn. Achieving the right model complexity is crucial for accurate predictions and reliable results.

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Mlearning.ai

APRIL 10, 2023

Supervised machine learning (such as SVM or GradientBoost) and deep learning models (such as CNN or RNN) can promise far superior performances when comparing them to clustering models however this can come at a greater cost with marginal rewards to the environment, end-user, and product owner of such technology.

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Pickl AI

FEBRUARY 2, 2023

AI algorithms can help retailers to optimize their supply chain processes by analyzing data such as shipping times, transit costs, and inventory levels. Predictive Analytics Retailers are using AI to analyze vast amounts of data to gain insights into consumer behaviour, market trends, and sales patterns.

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Pickl AI

SEPTEMBER 26, 2024

Operational Efficiency Automating processes such as inventory management or supply chain optimization reduces costs while improving overall productivity. Marketing Optimisation Utilising predictive analytics enables targeted marketing campaigns that resonate with specific customer segments, increasing conversion rates.

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IBM Journey to AI blog

OCTOBER 20, 2023

Artificial intelligence platforms enable individuals to create, evaluate, implement and update machine learning (ML) and deep learning models in a more scalable way. AI platform tools enable knowledge workers to analyze data, formulate predictions and execute tasks with greater speed and precision than they can manually.

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IBM Journey to AI blog

SEPTEMBER 6, 2023

AI marketing is the process of using AI capabilities like data collection, data-driven analysis, natural language processing (NLP) and machine learning (ML) to deliver customer insights and automate critical marketing decisions. What is AI marketing?

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Heartbeat

FEBRUARY 28, 2024

DistilBERT is chosen for its efficiency and effectiveness in handling natural language processing tasks, such as question answering. This pipeline is responsible for processing the context and question to generate an answer. Configure Model and Tokenizer Purpose: Select and load the DistilBERT model and its tokenizer.

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IBM Journey to AI blog

FEBRUARY 23, 2024

Beyond the simplistic chat bubble of conversational AI lies a complex blend of technologies, with natural language processing (NLP) taking center stage. Machine learning (ML) and deep learning (DL) form the foundation of conversational AI development.

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AWS Machine Learning Blog

JANUARY 30, 2023

Problem statement Machine learning has become an essential tool for extracting insights from large amounts of data. From image and speech recognition to natural language processing and predictive analytics, ML models have been applied to a wide range of problems.

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Mlearning.ai

MARCH 26, 2023

Once trained, the network can predict or decide on new, unseen data. Neural networks can be used for various tasks, including image and speech recognition, natural language processing, and predictive analytics. Picture from [link] Diving in further, specifically.

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IBM Journey to AI blog

MAY 17, 2024

A full one-third of consumers found their early customer support and chatbot experiences that use natural language processing (NLP) so disappointing that they didn’t want to engage with the technology again. And  And the centrality of these experiences isn’t limited to B2C vendors.

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IBM Journey to AI blog

FEBRUARY 14, 2024

Voice-based queries use natural language processing (NLP) and sentiment analysis for speech recognition so their conversations can begin immediately. Using machine learning (ML), AI can understand what customers are saying as well as their tone—and can direct them to customer service agents when needed.

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