Data Science Dojo

SEPTEMBER 8, 2023

Machine Learning and Deep Learning: The Power Duo Machine Learning (ML) and Deep Learning (DL) are two critical branches of AI that bring exceptional capabilities to predictive analytics. ML encompasses a range of algorithms that enable computers to learn from data without explicit programming. Streamline operations. Mitigate risks.

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Dataconomy

MARCH 13, 2025

These sophisticated algorithms facilitate a deeper understanding of data, enabling applications from image recognition to natural language processing. Deep learning is a subset of artificial intelligence that utilizes neural networks to process complex data and generate predictions. What is deep learning?

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Mlearning.ai

JUNE 7, 2023

This ability to understand long-range dependencies helps transformers better understand the context of words and achieve superior performance in natural language processing tasks. At the time, the NLP community was definitely starting to feel the buzz of these different advances. GPT-2 released with 1.5

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AWS Machine Learning Blog

SEPTEMBER 19, 2023

Amazon SageMaker Feature Store provides an end-to-end solution to automate feature engineering for machine learning (ML). For many ML use cases, raw data like log files, sensor readings, or transaction records need to be transformed into meaningful features that are optimized for model training. SageMaker Studio set up.

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AWS Machine Learning Blog

MAY 31, 2023

PyTorch is a machine learning (ML) framework based on the Torch library, used for applications such as computer vision and natural language processing. This provides a major flexibility advantage over the majority of ML frameworks, which require neural networks to be defined as static objects before runtime.

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Heartbeat

FEBRUARY 9, 2023

Photo by Brooks Leibee on Unsplash Introduction Natural language processing (NLP) is the field that gives computers the ability to recognize human languages, and it connects humans with computers. SpaCy is a free, open-source library written in Python for advanced Natural Language Processing.

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Dataconomy

APRIL 4, 2025

AI prompt engineering focuses on creating effective prompts that guide large language models to generate precise and relevant responses. Definition and role of AI prompt engineers AI prompt engineers are responsible for crafting and refining prompts used in AI models, including OpenAI’s ChatGPT and Google’s Bard.

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Flipboard

FEBRUARY 10, 2025

In this post, we dive into how organizations can use Amazon SageMaker AI , a fully managed service that allows you to build, train, and deploy ML models at scale, and can build AI agents using CrewAI, a popular agentic framework and open source models like DeepSeek-R1. This agent is equipped with a tool called BlocksCounterTool.

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AWS Machine Learning Blog

NOVEMBER 19, 2024

As an AI&ML Specialist, he focuses on Generative AI, Computer Vision, Reinforcement Learning and Anomaly Detection. Her interests include computer vision, natural language processing, and edge computing. Outside the tech world, he recharges by hitting the golf course and embarking on scenic hikes with his dog.

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AWS Machine Learning Blog

FEBRUARY 12, 2025

Large language models (LLMs) have revolutionized the field of natural language processing with their ability to understand and generate humanlike text. For this post, we use a dataset called sql-create-context , which contains samples of natural language instructions, schema definitions and the corresponding SQL query.

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Flipboard

NOVEMBER 17, 2023

Amazon SageMaker enables enterprises to build, train, and deploy machine learning (ML) models. Amazon SageMaker JumpStart provides pre-trained models and data to help you get started with ML. This type of data is often used in ML and artificial intelligence applications.

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Towards AI

FEBRUARY 20, 2024

Beginner’s Guide to ML-001: Introducing the Wonderful World of Machine Learning: An Introduction Everyone is using mobile or web applications which are based on one or other machine learning algorithms. Machine learning(ML) is evolving at a very fast pace. Photo by Andrea De Santis on Unsplash So, What is Machine Learning?

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Flipboard

JUNE 3, 2025

Approval workflows streamline model training and deployment processes, and AWS cross-account deployment enables resource allocation across organizational boundaries. The framework uses templates with Hugging Face text classification models, enabling rapid deployment of natural language processing capabilities.

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Dataconomy

MARCH 27, 2023

Both have the potential to transform the way organizations operate, enabling them to streamline processes, improve efficiency, and drive business outcomes. However, while RPA and ML share some similarities, they differ in functionality, purpose, and the level of human intervention required. What is machine learning (ML)?

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AWS Machine Learning Blog

NOVEMBER 1, 2024

Fine-tuning is a powerful approach in natural language processing (NLP) and generative AI , allowing businesses to tailor pre-trained large language models (LLMs) for specific tasks. This process involves updating the model’s weights to improve its performance on targeted applications. with a default value of 1.0.

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Dataconomy

MARCH 5, 2025

Definition of smart machines Smart machines integrate AI, ML, and deep learning for cognitive functionalities such as reasoning, decision-making, and autonomous actions. Core technologies Neural networks: These frameworks mimic brain functions, allowing machines to process information and learn from data interactions.

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AWS Machine Learning Blog

OCTOBER 11, 2024

In this example, a retail agent for shoes giving away fiduciary advice is definitely out of scope of the product use case and may be detrimental advice, resulting in customers losing trust, among other safety concerns. His area of research is all things natural language (like NLP, NLU, and NLG).

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The MLOps Blog

MARCH 21, 2023

From gathering and processing data to building models through experiments, deploying the best ones, and managing them at scale for continuous value in production—it’s a lot. As the number of ML-powered apps and services grows, it gets overwhelming for data scientists and ML engineers to build and deploy models at scale.

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Flipboard

MAY 28, 2025

Text-to-SQL for genomics data Text-to-SQL is a task in natural language processing (NLP) to automatically convert natural language text into SQL queries. This involves translating the written text into a structured format and using it to generate an accurate SQL query that can run on a database.

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AWS Machine Learning Blog

MAY 8, 2023

SageMaker provides single model endpoints (SMEs), which allow you to deploy a single ML model, or multi-model endpoints (MMEs), which allow you to specify multiple models to host behind a logical endpoint for higher resource utilization. About the Authors Melanie Li is a Senior AI/ML Specialist TAM at AWS based in Sydney, Australia.

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Dataconomy

FEBRUARY 28, 2024

Unlike traditional software that sticks to rigid instructions, ML systems analyze data and identify patterns. Dialogflow gives you the tools for granular control, thanks to its powerful natural language processing capabilities Sales and marketing Another area where you can integrate AI at work is sales and marketing.

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AWS Machine Learning Blog

OCTOBER 6, 2023

Large language models (LLMs) are revolutionizing fields like search engines, natural language processing (NLP), healthcare, robotics, and code generation. One such component is a feature store, a tool that stores, shares, and manages features for machine learning (ML) models.

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How to Learn Machine Learning

MAY 2, 2025

Azure Machine Learning is Microsoft’s enterprise-grade service that provides a comprehensive environment for data scientists and ML engineers to build, train, deploy, and manage machine learning models at scale. You can explore its capabilities through the official Azure ML Studio documentation. Awesome, right?

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Dataconomy

JULY 23, 2024

Runa Capital’s ROSS Index , the definitive ranking of the fastest-growing open-source startups, has just dropped its Q2 2024 edition, and it’s a captivating snapshot of where this vital sector is headed. This isn’t surprising, considering the AI gold rush underway in the broader tech landscape.

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AWS Machine Learning Blog

NOVEMBER 14, 2024

Through natural language processing algorithms and machine learning techniques, the large language model (LLM) analyzes the user’s queries in real time, extracting relevant context and intent to deliver tailored responses. The class definition is similar to the LangChain ConversationalChatAgent class.

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Pickl AI

JANUARY 29, 2024

2024 Tech breakdown: Understanding Data Science vs ML vs AI Quoting Eric Schmidt , the former CEO of Google, ‘There were 5 exabytes of information created between the dawn of civilisation through 2003, but that much information is now created every two days.’ AI comprises Natural Language Processing, computer vision, and robotics.

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AWS Machine Learning Blog

FEBRUARY 25, 2025

Instead of relying on predefined, rigid definitions, our approach follows the principle of understanding a set. Its important to note that the learned definitions might differ from common expectations. Model invocation We use Anthropics Claude 3 Sonnet model for the natural language processing task.

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Towards AI

AUGUST 25, 2023

As a reminder, I highly recommend that you refer to more than one resource (other than documentation) when learning ML, preferably a textbook geared toward your learning level (beginner/intermediate / advanced). In ML, there are a variety of algorithms that can help solve problems. Speech and Language Processing.

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Smart Data Collective

JULY 23, 2021

If you’ve been looking for ways to boost your live broadcast strategies, this is definitely a great way to do it! To perform its function , a chatbot will use advanced machine learning and natural language processing algorithms. Quality chatbots have definitely changed the game. What Is a Chatbot?

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AWS Machine Learning Blog

JUNE 25, 2024

Businesses can use LLMs to gain valuable insights, streamline processes, and deliver enhanced customer experiences. Although these traditional machine learning (ML) approaches might perform decently in terms of accuracy, there are several significant advantages to adopting generative AI approaches.

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AWS Machine Learning Blog

OCTOBER 24, 2024

The agent can generate SQL queries using natural language questions using a database schema DDL (data definition language for SQL) and execute them against a database instance for the database tier. His area of research is all things natural language (like NLP, NLU, NLG).

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Towards AI

AUGUST 16, 2023

In fact, AI/ML graduate textbooks do not provide a clear and consistent description of the AI software engineering process. Therefore, I thought it would be helpful to give a complete description of the AI engineering process or AI Process, which is described in most AI/ML textbooks [5][6].

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AWS Machine Learning Blog

APRIL 16, 2024

Amazon SageMaker Studio provides a fully managed solution for data scientists to interactively build, train, and deploy machine learning (ML) models. In the process of working on their ML tasks, data scientists typically start their workflow by discovering relevant data sources and connecting to them.

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AWS Machine Learning Blog

APRIL 11, 2025

To delete the resources deployed to your AWS account through AWS SAM, run the following command: sam delete OpenAPI schema definition After the custom plugin is deployed, Amazon Q Business will process a users prompt and use the OpenAPI schema to dynamically determine the appropriate APIs to call to accomplish the users goal.

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AWS Machine Learning Blog

APRIL 29, 2024

Historically, natural language processing (NLP) would be a primary research and development expense. In 2024, however, organizations are using large language models (LLMs), which require relatively little focus on NLP, shifting research and development from modeling to the infrastructure needed to support LLM workflows.

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AWS Machine Learning Blog

MAY 22, 2025

This feature uses natural language processing to identify the most important concepts, facts, and insights within text documents, then generates concise summaries that preserve the essential meaning while significantly reducing reading time.

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Towards AI

AUGUST 28, 2023

Apply these concepts to solve real-world industry problems in deep learning Taking a step away from classical machine learning (ML), embeddings are at the core of most deep learning (DL) use cases. Embeddings have created a notable impact on several areas of applications today, including Large Language Models (LLMs).

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