Heartbeat

FEBRUARY 8, 2023

Source: Author The field of natural language processing (NLP), which studies how computer science and human communication interact, is rapidly growing. By enabling robots to comprehend, interpret, and produce natural language, NLP opens up a world of research and application possibilities.

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Heartbeat

JULY 18, 2023

Source: Author Natural Language Processing (NLP) is a field of study focused on allowing computers to understand and process human language. There are many different NLP techniques and tools available, including the R programming language.

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Data Science Dojo

AUGUST 27, 2024

In essence, data scientists use their skills to turn raw data into valuable information that can be used to improve products, services, and business strategies. Meaningful Insights: Statistics helps to extract valuable information from the data, turning raw numbers into actionable insights. It’s like deciphering a secret code.

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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. These techniques enable businesses to respond quickly to customer inquiries, optimize pricing strategies, and automate the quotation generation process.

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Pickl AI

JANUARY 2, 2025

Summary: Entropy in Machine Learning quantifies uncertainty, driving better decision-making in algorithms. It optimises decision trees, probabilistic models, clustering, and reinforcement learning. Key Takeaways Entropy measures randomness, guiding algorithms to make better decisions.

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Dataconomy

APRIL 4, 2023

Some of the common types are: Linear Regression Deep Neural Networks Logistic Regression Decision Trees AI Linear Discriminant Analysis Naive Bayes Support Vector Machines Learning Vector Quantization K-nearest Neighbors Random Forest What do they mean? The information from previous decisions is analyzed via the decision tree.

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Dataconomy

APRIL 4, 2023

Some of the common types are: Linear Regression Deep Neural Networks Logistic Regression Decision Trees AI Linear Discriminant Analysis Naive Bayes Support Vector Machines Learning Vector Quantization K-nearest Neighbors Random Forest What do they mean? The information from previous decisions is analyzed via the decision tree.

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Towards AI

FEBRUARY 20, 2024

Linear Regression Decision Trees Support Vector Machines Neural Networks Clustering Algorithms (e.g., Linear Regression Decision Trees Support Vector Machines Neural Networks Clustering Algorithms (e.g., Models trained on sensitive data may inadvertently leak private information. Models […]

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Dataconomy

AUGUST 31, 2023

The classification model learns from the training data, identifying the distinguishing characteristics between each class, enabling it to make informed predictions. For example, in text classification, a piece of text can be classified as both “sports” and “politics” if it contains information related to both topics.

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Pickl AI

DECEMBER 9, 2024

In contrast, decision trees assume data can be split into homogeneous groups through feature thresholds. Inductive bias is crucial in ensuring that Machine Learning models can learn efficiently and make reliable predictions even with limited information by guiding how they make assumptions about the data.

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Dataconomy

MAY 25, 2023

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. This enables them to extract valuable insights, identify patterns, and make informed decisions in real-time.

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Pickl AI

SEPTEMBER 16, 2024

Summary: This blog highlights ten crucial Machine Learning algorithms to know in 2024, including linear regression, decision trees, and reinforcement learning. Decision Trees These are a versatile supervised learning algorithm used for both classification and regression tasks.

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Dataconomy

JUNE 13, 2023

Making the right decisions in an aggressive market is crucial for your business growth and that’s where decision intelligence (DI) comes to play. In this era of information overload, utilizing the power of data and technology has become paramount to drive effective decision-making. What is decision intelligence?

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Pickl AI

JULY 12, 2024

Deep Learning has been used to achieve state-of-the-art results in a variety of tasks, including image recognition, Natural Language Processing, and speech recognition. Natural Language Processing (NLP) This is a field of computer science that deals with the interaction between computers and human language.

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Chatbots Life

MAY 16, 2023

By integrating generative AI, chatbots can generate more natural and human-like responses, allowing for a more engaging and satisfying user experience. Simple chatbots without generative AI integration rely on pre-programmed responses and rule-based decision trees to guide their interactions with users.

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Dataconomy

MARCH 13, 2023

With advances in machine learning, deep learning, and natural language processing, the possibilities of what we can create with AI are limitless. However, the process of creating AI can seem daunting to those who are unfamiliar with the technicalities involved. What is required to build an AI system?

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AWS Machine Learning Blog

DECEMBER 22, 2023

Generative AI agents are capable of producing human-like responses and engaging in natural language conversations by orchestrating a chain of calls to foundation models (FMs) and other augmenting tools based on user input. In this post, we demonstrate how to build a generative AI financial services agent powered by Amazon Bedrock.

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Pickl AI

AUGUST 1, 2023

Machine Learning models play a crucial role in this process, serving as the backbone for various applications, from image recognition to natural language processing. Examples of supervised learning models include linear regression, decision trees, support vector machines, and neural networks.

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Pickl AI

APRIL 9, 2025

These include: Reasoning: Drawing logical conclusions from information. Language Understanding: Processing and interpreting human language (Natural Language Processing – NLP). Knowledge Representation: Storing and organizing information effectively. What kind of tasks?

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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. Rule-based chatbots : Also known as decision-tree or script-driven bots, they follow preprogrammed protocols and generate responses based on predefined rules.

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Pickl AI

FEBRUARY 18, 2025

Summary : Sentiment Analysis is a natural language processing technique that interprets and classifies emotions expressed in text. Sentiment Analysis is a popular task in natural language processing. It uses various Natural Language Processing algorithms such as Rule-based, Automatic, and Hybrid.

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IBM Journey to AI blog

SEPTEMBER 5, 2023

However, more advanced chatbots can leverage artificial intelligence (AI) and natural language processing (NLP) to understand a user’s input and navigate complex human conversations with ease. Essentially, these chatbots operate like a decision tree.

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Heartbeat

APRIL 17, 2023

One of the goals of ML is to enable computers to process and analyze data in a way that is similar to how humans process information. Human brains are capable of processing vast amounts of information from the environment and making complex decisions based on that information. noun, verb, adjective).

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Pickl AI

OCTOBER 18, 2023

Every day, companies generate and collect vast amounts of data, ranging from customer information to market trends. Data serves as the backbone of informed decision-making, and the accuracy, consistency, and reliability of data directly impact an organization’s operations, strategy, and overall performance.

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Heartbeat

OCTOBER 11, 2023

Handling Complex and Large Datasets: Machine learning algorithms can handle vast amounts of data and extract meaningful information. Deep learning is utilized in many fields, such as robotics, speech recognition, computer vision, and natural language processing.

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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.’

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Pickl AI

FEBRUARY 7, 2025

The training process involves feeding data into a model, allowing it to make predictions or classify information based on patterns observed. Deep Learning is a subset of Machine Learning that mimics how humans process information using neural networks. What is Deep Learning? billion by 2034.

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Pickl AI

SEPTEMBER 12, 2024

By understanding crucial concepts like Machine Learning, Data Mining, and Predictive Modelling, analysts can communicate effectively, collaborate with cross-functional teams, and make informed decisions that drive business success. Join us as we explore the language of Data Science and unlock your potential as a Data Analyst.

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AWS Machine Learning Blog

OCTOBER 30, 2024

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

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Mlearning.ai

FEBRUARY 15, 2023

Introduction In natural language processing, text categorization tasks are common (NLP). Some important things that were considered during these selections were: Random Forest : The ultimate feature importance in a Random forest is the average of all decision tree feature importance. Uysal and Gunal, 2014).

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Heartbeat

MAY 29, 2023

LLMs are one of the most exciting advancements in natural language processing (NLP). Part 1: Training LLMs Language models have become increasingly important in natural language processing (NLP) applications, and LLMs like GPT-3 have proven to be particularly successful in generating coherent and meaningful text.

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Chatbots Life

SEPTEMBER 11, 2023

Whether engaging in informal chats or crafting professional documents, conveying our thoughts effectively relies on the precision of our language. This limitation has paved the way for more advanced solutions that harness the power of Natural Language Processing (NLP).

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Pickl AI

OCTOBER 24, 2024

Reasoning : AI systems analyse data and draw logical conclusions, helping them make informed decisions. Virtual Assistants : AI-driven assistants like Siri and Alexa help users manage daily tasks using natural language processing. From virtual assistants to healthcare diagnostics, AI’s impact is growing rapidly.

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IBM Journey to AI blog

JULY 6, 2023

Machine learning can then “learn” from the data to create insights that improve performance or inform predictions. Machine learning engineers can specialize in natural language processing and computer vision, become software engineers focused on machine learning and more.

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Pickl AI

JULY 23, 2023

Exploring Four Types of Analytics: Examples, Explanation, and Applications In today’s data-driven world, analytics has become a crucial aspect of decision-making across various industries. Data, in its most fundamental form, refers to any information, facts, or statistics collected for analysis or reference. What is Data?

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Pickl AI

NOVEMBER 18, 2024

Natural language processing ( NLP ) allows machines to understand, interpret, and generate human language, which powers applications like chatbots and voice assistants. For example, linear regression is typically used to predict continuous variables, while decision trees are great for classification and regression tasks.

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Pickl AI

NOVEMBER 5, 2024

AI encompasses various subfields, including Machine Learning (ML), Natural Language Processing (NLP), robotics, and computer vision. Together, Data Science and AI enable organisations to analyse vast amounts of data efficiently and make informed decisions based on predictive analytics.

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