Analytics Vidhya

DECEMBER 30, 2022

Introduction Natural language processing (NLP) is a field of computer science and artificial intelligence that focuses on the interaction between computers and human (natural) languages. Natural language processing (NLP) is […].

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Pickl AI

JULY 26, 2023

The concepts of bias and variance in Machine Learning are two crucial aspects in the realm of statistical modelling and machine learning. Understanding these concepts is paramount for any data scientist, machine learning engineer, or researcher striving to build robust and accurate models.

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IBM Journey to AI blog

JULY 6, 2023

While data science and machine learning are related, they are very different fields. In a nutshell, data science brings structure to big data while machine learning focuses on learning from the data itself. What is machine learning? This post will dive deeper into the nuances of each field.

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Data Science Dojo

MAY 24, 2023

Machine learning practices are the guiding principles that transform raw data into powerful insights. By following best practices in algorithm selection, data preprocessing, model evaluation, and deployment, we unlock the true potential of machine learning and pave the way for innovation and success.

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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. ML catalyses AI advancements, enabling systems to evolve and improve decision-making.

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ODSC - Open Data Science

AUGUST 15, 2023

Full-Stack Machine Learning for Data Scientists Hugo Bowne-Anderson, PhD | Head of Data Science Evangelism and Marketing | Outerbounds This session will address the issue of how to make the life cycle of a machine learning project a repeatable process. Check out a few of them below.

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Dataconomy

JULY 18, 2023

AI techniques for real-time quoting AI Techniques for Real-Time Quoting involve various technologies and algorithms that leverage machine learning, natural language processing, and predictive analytics to generate accurate and timely quotations.

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Pickl AI

NOVEMBER 8, 2023

The Scikit-Learn cheat sheet is a concise reference guide for using Scikit-Learn , a popular Machine Learning library in Python. It offers quick access to key functions and concepts, including data preprocessing, supervised and unsupervised learning techniques, and model evaluation.

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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. It can be employed for both regression and classification tasks.

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ODSC - Open Data Science

SEPTEMBER 18, 2023

A lot goes into learning a new skill, regardless of how in-depth it is. Getting started with natural language processing (NLP) is no exception, as you need to be savvy in machine learning, deep learning, language, and more.

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Dataconomy

AUGUST 31, 2023

Classification in machine learning involves the intriguing process of assigning labels to new data based on patterns learned from training examples. Machine learning models have already started to take up a lot of space in our lives, even if we are not consciously aware of it.

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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. Now let’s delve into the details.

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Dataconomy

JUNE 13, 2023

At its core, decision intelligence involves collecting and integrating relevant data from various sources, such as databases, text documents, and APIs. This data is then analyzed using statistical methods, machine learning algorithms, and data mining techniques to uncover meaningful patterns and relationships.

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Pickl AI

MAY 24, 2023

This may include for instance in Machine Learning, Data Science, Data Visualisation, image and Data Manipulation. As the collection of Python libraries are huge, you might be faced with the need to make difficult decision on which library to choose from. What to consider when choosing a Python Library?

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Heartbeat

APRIL 17, 2023

Photo by Shahadat Rahman on Unsplash Introduction Machine learning (ML) focuses on developing algorithms and models that can learn from data and make predictions or decisions. 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.

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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. You must have defined your /.comet.yml

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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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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. What are code and usage?

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Pickl AI

MAY 31, 2023

Accordingly, there are many Python libraries which are open-source including Data Manipulation, Data Visualisation, Machine Learning, Natural Language Processing , Statistics and Mathematics. Learn probability, testing for hypotheses, regression, classification, and grouping, among other topics.

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Dataconomy

MAY 25, 2023

Simultaneously, artificial intelligence has revolutionized the way machines learn, reason, and make decisions. On the other hand, artificial intelligence is the simulation of human intelligence in machines that are programmed to think and learn like humans.

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Pickl AI

JULY 14, 2023

Machine Learning and Neural Networks (1990s-2000s): Machine Learning (ML) became a focal point, enabling systems to learn from data and improve performance without explicit programming. Techniques such as decision trees, support vector machines, and neural networks gained popularity.

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IBM Journey to AI blog

DECEMBER 20, 2023

Machine learning (ML) technologies can drive decision-making in virtually all industries, from healthcare to human resources to finance and in myriad use cases, like computer vision , large language models (LLMs), speech recognition, self-driving cars and more. What is machine learning?

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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

FEBRUARY 22, 2023

Deep learning for feature extraction, ensemble models, and more Photo by DeepMind on Unsplash The advent of deep learning has been a game-changer in machine learning, paving the way for the creation of complex models capable of feats previously thought impossible.

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Pickl AI

JULY 18, 2023

Additionally, its natural language processing capabilities and Machine Learning frameworks like TensorFlow and scikit-learn make Python an all-in-one language for Data Science. It includes statistical analysis, predictive modeling, Machine Learning, and data mining techniques.

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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. NLP translates the user’s words into machine actions, enabling machines to understand and respond to customer inquiries accurately.

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Pickl AI

SEPTEMBER 7, 2023

Machine Learning models can leave you spellbound by their efficiency and proficiency. When you start exploring more about Machine Learning, you will come across the Gradient Boosting Algorithm. Basically, it is a powerful and versatile machine-learning algorithm that falls under the category of ensemble learning.

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Pickl AI

MAY 10, 2023

Machine Learning is a subset of Artificial Intelligence and Computer Science that makes use of data and algorithms to imitate human learning and improving accuracy. While Classification is an example of directed Machine Learning technique, Clustering is an unsupervised Machine Learning algorithm.

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Dataconomy

APRIL 4, 2023

Artificial Intelligence (AI) models are the building blocks of modern machine learning algorithms that enable machines to learn and perform complex tasks. These models are designed to replicate the human brain’s cognitive functions, enabling them to perceive, reason, learn, and make decisions based on data.

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Dataconomy

APRIL 4, 2023

Artificial Intelligence (AI) models are the building blocks of modern machine learning algorithms that enable machines to learn and perform complex tasks. These models are designed to replicate the human brain’s cognitive functions, enabling them to perceive, reason, learn, and make decisions based on data.

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Cambridge Intelligence

FEBRUARY 20, 2024

Experienced analysts and investigators have an important part to play at every stage, as do advanced technologies like AI and machine learning. But to improve the speed, accuracy and effectiveness of decision making, there’s been a rise in the usage of AI technologies and machine learning.

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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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Mlearning.ai

FEBRUARY 15, 2023

Introduction In natural language processing, text categorization tasks are common (NLP). Figure 1 Preprocessing Data preprocessing is an essential step in building a Machine Learning model. We also need to process the utterance_text column in order to reduce text dimensions. Uysal and Gunal, 2014).

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Pickl AI

AUGUST 23, 2023

By extracting insights from these datasets, professionals can make more informed investment decisions, reducing the risk associated with emotional biases. Through sophisticated algorithms and Machine Learning models , data scientists can predict stock price movements with a degree of accuracy that was previously unthinkable.

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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. The models are powered by advanced Deep Learning and Machine Learning research. What is Text Summarization for NLP?

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Chatbots Life

SEPTEMBER 11, 2023

This limitation has paved the way for more advanced solutions that harness the power of Natural Language Processing (NLP). This has spurred the development of more advanced solutions powered by Natural Language Processing (NLP) that offer a more comprehensive approach to language-related tasks.

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Pickl AI

JULY 10, 2023

R is a popular programming language and environment widely used in the field of data science. It provides a comprehensive suite of tools, libraries, and packages specifically designed for statistical analysis, data manipulation, visualization, and machine learning.

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