Data Science Dojo

AUGUST 27, 2024

Algorithms: Decision trees, random forests, logistic regression, and more are like different techniques a detective might use to solve a case. Algorithms: Decision trees, random forests, logistic regression, and more are like different techniques a detective might use to solve a case.

Data Scientist 195

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Towards AI

SEPTEMBER 5, 2024

Meme shared by ghost_in_the_machine TAI Curated section Article of the week Let’s Create an Agentic Multimodal Chatbot from Scratch by Arthur Lagacherie Have you ever wondered how to create a truly agentic multimodal chatbot from scratch? Our must-read articles 1. Meme of the week!

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Algorithm ML ML Machine Learning 86

Dataconomy

APRIL 4, 2023

Artificial intelligence (AI) is a broad term that encompasses the ability of computers and machines to perform tasks that normally require human intelligence, such as reasoning, learning, decision-making, and problem-solving. Decision Trees AI This AI methodology is not only easy to understand but also quite effective.

K-nearest Neighbors 91

K-nearest Neighbors Decision Trees AI AI 91

Dataconomy

APRIL 4, 2023

Artificial intelligence (AI) is a broad term that encompasses the ability of computers and machines to perform tasks that normally require human intelligence, such as reasoning, learning, decision-making, and problem-solving. Decision Trees AI This AI methodology is not only easy to understand but also quite effective.

K-nearest Neighbors 91

K-nearest Neighbors Decision Trees AI AI 91

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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Dataconomy

AUGUST 31, 2023

Natural Language Processing (NLP) : Classification can be applied to text data to categorize messages, emails, or social media posts into different categories, such as spam vs. non-spam, positive vs. negative sentiment, or topic classification.

Machine Learning 136

Machine Learning Machine Learning Supervised Learning Algorithm 136

ODSC - Open Data Science

AUGUST 15, 2023

You’ll get hands-on practice with unsupervised learning techniques, such as K-Means clustering, and classification algorithms like decision trees and random forest. Originally posted on OpenDataScience.com Read more data science articles on OpenDataScience.com , including tutorials and guides from beginner to advanced levels!

Machine Learning 52

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Dataconomy

MAY 25, 2023

In the subsequent sections of this article, we will explore the challenges and limitations associated with artificial intelligence in IoT, as well as the key technologies and techniques driving this convergence. These advantages have a transformative impact across various industries and domains.

Internet of Things 160

Internet of Things Artificial Intelligence Artificial Intelligence AI 160

AssemblyAI

NOVEMBER 9, 2023

In Natural Language Processing (NLP), Text Summarization models automatically shorten documents, papers, podcasts, videos, and more into their most important soundbites. High variance means overfitting models with high flexibility tend to have high variance like decision trees. What is Text Summarization for NLP?

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ODSC - Open Data Science

SEPTEMBER 18, 2023

Getting started with natural language processing (NLP) is no exception, as you need to be savvy in machine learning, deep learning, language, and more. Unlock the power of language, learn how machines can understand, interpret, and generate human language, and embark on this exciting journey into the world of NLP.

Deep Learning 52

Deep Learning Deep Learning Machine Learning Machine Learning 52

Chatbots Life

SEPTEMBER 11, 2023

Introduction The article explores the practical application of essential Python libraries like TextBlob, symspell, pyspellchecker and Flan-T5 based grammar checker in the context of spell and grammar checking. Learning Objectives: In this article, we will understand the following: What are the spell checker and grammar checker?

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Heartbeat

APRIL 17, 2023

Named entity recognition (NER) is a subtask of natural language processing (NLP) that involves automatically identifying and classifying named entities mentioned in a text. In this article, we will discuss how to perform Named Entity Recognition with SpaCy , a popular Python library for NLP. synonyms).

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Pickl AI

NOVEMBER 18, 2024

The article also addresses challenges like data quality and model complexity, highlighting the importance of ethical considerations in Machine Learning applications. Natural language processing ( NLP ) allows machines to understand, interpret, and generate human language, which powers applications like chatbots and voice assistants.

Machine Learning 52

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Pickl AI

NOVEMBER 8, 2023

Scikit-Learn is a robust library in Python that simplifies the process of building Machine Learning models. In this article, we will explore the Scikit-Learn Cheat Sheet, an essential resource for anyone looking to leverage this powerful library. Can I use Scikit-Learn for natural language processing (NLP)?

Machine Learning 52

Machine Learning Machine Learning Data Science Python 52

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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Pickl AI

OCTOBER 18, 2023

In this article, we delve into the significance of data quality, how organizations are leveraging various tools to enhance it, and the transformative power of Artificial Intelligence (AI) and Machine Learning (ML) in elevating data quality to new heights. – Natural Language Processing (NLP) for text data standardization.

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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. 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.

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IBM Journey to AI blog

JULY 6, 2023

Subcategories of machine learning Some of the most commonly used machine learning algorithms include linear regression , logistic regression, decision tree , Support Vector Machine (SVM) algorithm, Naïve Bayes algorithm and KNN algorithm. These can be supervised learning, unsupervised learning or reinforced/reinforcement learning.

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Machine Learning Machine Learning Data Science Big Data 70

Pickl AI

OCTOBER 24, 2024

Summary: This article compares Artificial Intelligence (AI) vs Machine Learning (ML), clarifying their definitions, applications, and key differences. This article compares Artificial Intelligence vs Machine Learning to clarify their distinctions. From virtual assistants to healthcare diagnostics, AI’s impact is growing rapidly.

Artificial Intelligence 52

Artificial Intelligence Artificial Intelligence Machine Learning Machine Learning 52

Heartbeat

MAY 29, 2023

LLMs are one of the most exciting advancements in natural language processing (NLP). LLMs like GPT-3 and T5 have already shown promising results in various NLP tasks such as language translation, question-answering, and summarization. Boosting can help to improve the accuracy and generalization of the final model.

Machine Learning 78

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Heartbeat

FEBRUARY 22, 2023

These models have been used to achieve state-of-the-art performance in many different fields, including image classification, natural language processing, and speech recognition. This article delves into using deep learning to enhance the effectiveness of classic ML models.

Deep Learning 52

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How to Learn Machine Learning

DECEMBER 4, 2022

Programming a computer with artificial intelligence (Ai) allows it to make decisions on its own. Numerous techniques, such as but not limited to rule-based systems, decision trees, genetic algorithms, artificial neural networks, and fuzzy logic systems, can be used to do this.

AI 52

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Pickl AI

AUGUST 23, 2023

This article delves into the pivotal role of Data Science in stock market analysis, discussing key takeaways that highlight its significance. Key Takeaways Data-Driven Decision Making The role of Data Science in stock market analysis is growing.

Data Science 52

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Pickl AI

NOVEMBER 5, 2024

These statistics underscore the significant impact that Data Science and AI are having on our future, reshaping how we analyse data, make decisions, and interact with technology. AI encompasses various subfields, including Machine Learning (ML), Natural Language Processing (NLP), robotics, and computer vision.

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Pickl AI

JULY 26, 2023

Gender Bias in Natural Language Processing (NLP) NLP models can develop biases based on the data they are trained on. Random Forest Overfitting Random Forests are designed to reduce overfitting compared to decision trees, but if the number of trees is too high, it can lead to high variance.

Machine Learning 52

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Pickl AI

SEPTEMBER 30, 2024

This article explores how ML reshapes business operations, improves decision-making, and fuels growth, highlighting why understanding its impact is crucial for staying ahead in today’s competitive landscape. Key concepts in ML are: Algorithms : Algorithms are the mathematical instructions that guide the learning process.

Machine Learning 52

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Pickl AI

JULY 18, 2023

There are different programming languages and in this article, we will explore 8 programming languages that play a crucial role in the realm of Data Science. 8 Most Used Programming Languages for Data Science 1. Python: Versatile and Robust Python is one of the future programming languages for Data Science.

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Pickl AI

SEPTEMBER 23, 2024

Introduction Artificial Intelligence (AI) and Data Science are revolutionising how we analyse data, make decisions, and solve complex problems. The synergy between AI and Data Science enhances data-driven decision-making, powering innovations across healthcare, finance, and technology industries.

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DagsHub

DECEMBER 23, 2024

They are: Based on shallow, simple, and interpretable machine learning models like support vector machines (SVMs), decision trees, or k-nearest neighbors (kNN). Relies on explicit decision boundaries or feature representations for sample selection. You can explore more on this topic in this article by Lilian Weng or this one.

Deep Learning 52

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Mlearning.ai

FEBRUARY 6, 2023

In this article, I am to break down some of these issues around model-based chatbot detection. Is this different from summarizing articles online? One such model could be Neural Prototype Trees [11], a model architecture that makes a decision tree off of “prototypes,” or interpretable representations of patterns in data.

AI 52

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IBM Journey to AI blog

JUNE 5, 2024

If, for instance, a development team wants to understand which app features most significantly impact retention, it might use AI-driven natural language processing (NLP) to analyze unstructured data. News apps, for instance, can highlight articles similar to the ones a user has previously read and liked.

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