Mlearning.ai

APRIL 8, 2023

Charting the evolution of SOTA (State-of-the-art) techniques in NLP (Natural Language Processing) over the years, highlighting the key algorithms, influential figures, and groundbreaking papers that have shaped the field. Evolution of NLP Models To understand the full impact of the above evolutionary process.

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Towards AI

JULY 20, 2023

Natural Language Processing Getting desirable data out of published reports and clinical trials and into systematic literature reviews (SLRs) — a process known as data extraction — is just one of a series of incredibly time-consuming, repetitive, and potentially error-prone steps involved in creating SLRs and meta-analyses.

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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. In this blog, we will delve into the fundamental concepts of data model for Machine Learning, exploring their types. What is Machine Learning?

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Towards AI

APRIL 27, 2023

Understanding the Principles, Challenges, and Applications of Gradient Descent Image by Author with @MidJourney Introduction to Gradient Descent Gradient descent is a fundamental optimization algorithm used in machine learning and data science to find the optimal values of the parameters in a model.

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Pickl AI

JULY 12, 2024

Their interactive nature makes them suitable for experimenting with AI algorithms and analysing data. Here are a few of the key concepts that you should know: Machine Learning (ML) This is a type of AI that allows computers to learn without being explicitly programmed.

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IBM Journey to AI blog

DECEMBER 20, 2023

Each type and sub-type of ML algorithm has unique benefits and capabilities that teams can leverage for different tasks. What is machine learning? Instead of using explicit instructions for performance optimization, ML models rely on algorithms and statistical models that deploy tasks based on data patterns and inferences.

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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. You might be using machine learning algorithms from everything you see on OTT or everything you shop online.

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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. Markets for each field are booming, offering diverse job roles, especially in Machine Learning for Data Analytics.

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Mlearning.ai

JUNE 14, 2023

Learning LLMs (Foundational Models) Base Knowledge / Concepts: What is AI, ML and NLP Introduction to ML and AI — MFML Part 1 — YouTube What is NLP (Natural Language Processing)? — YouTube YouTube Introduction to Natural Language Processing (NLP) NLP 2012 Dan Jurafsky and Chris Manning (1.1)

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Heartbeat

MARCH 8, 2023

Source: Author Introduction Text classification, which involves categorizing text into specified groups based on its content, is an important natural language processing (NLP) task. R has a rich set of libraries and tools for machine learning and natural language processing, making it well-suited for spam detection tasks.

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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. synonyms).

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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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Dataconomy

AUGUST 31, 2023

Here are some examples of where classification can be used in machine learning: Image recognition : Classification can be used to identify objects within images. Unsupervised learning Unsupervised learning is a type of machine learning where the algorithm tries to find patterns or relationships in the data without the use of labeled data.

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Pickl AI

SEPTEMBER 10, 2024

Read More: Learn Top 10 Deep Learning Algorithms in Machine Learning Top 10 Fascinating Applications of Deep Learning You Should Know Basics of the Perceptron At its core, a Perceptron is a type of artificial neuron that takes multiple inputs, applies weights to them, and produces a single output.

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Pickl AI

NOVEMBER 28, 2024

Summary: The blog discusses essential skills for Machine Learning Engineer, emphasising the importance of programming, mathematics, and algorithm knowledge. Key programming languages include Python and R, while mathematical concepts like linear algebra and calculus are crucial for model optimisation.

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Pickl AI

AUGUST 1, 2023

Text mining is also known as text analytics or Natural Language Processing (NLP). It is the process of deriving valuable patterns, trends, and insights from unstructured textual data. Sentiment analysis techniques range from rule-based approaches to more advanced machine learning algorithms.

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Heartbeat

OCTOBER 11, 2023

A key component of artificial intelligence is training algorithms to make predictions or judgments based on data. This process is known as machine learning or deep learning. Two of the most well-known subfields of AI are machine learning and deep learning. What is Machine 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. Being an important component of Data Science, the use of statistical methods are crucial in training algorithms in order to make classification.

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Dataconomy

JUNE 13, 2023

Decision intelligence is not just about crunching numbers or relying on algorithms; it is about unlocking the true potential of data to make smarter choices and fuel business success. Think of decision intelligence as a synergy between the human mind and cutting-edge algorithms. What is decision intelligence?

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How to Learn Machine Learning

JANUARY 21, 2023

With the advent of artificial intelligence (AI) and natural language processing (NLP) , creating a virtual personal assistant has become more achievable than ever before. This can be done using a combination of voice recognition, text-to-speech, and natural language processing to create an interactive experience.

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Pickl AI

NOVEMBER 18, 2024

Key Takeaways Machine Learning Models are vital for modern technology applications. Key steps involve problem definition, data preparation, and algorithm selection. Ethical considerations are crucial in developing fair Machine Learning solutions. Let’s break down the key components and types of Machine Learning.

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Mlearning.ai

JULY 4, 2023

One such intriguing aspect is the potential to predict a user’s race based on their tweets, a task that merges the realms of Natural Language Processing (NLP), machine learning, and sociolinguistics.

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Dataconomy

MAY 25, 2023

On the other hand, artificial intelligence is the simulation of human intelligence in machines that are programmed to think and learn like humans. 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.

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Pickl AI

SEPTEMBER 30, 2024

Key concepts in ML are: Algorithms : Algorithms are the mathematical instructions that guide the learning process. They process data, identify patterns, and adjust the model accordingly. Common algorithms include decision trees, neural networks, and support vector machines.

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Heartbeat

OCTOBER 23, 2023

The Role of Data Scientists and ML Engineers in Health Informatics At the heart of the Age of Health Informatics are data scientists and ML engineers who play a critical role in harnessing the power of data and developing intelligent algorithms.

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IBM Journey to AI blog

JULY 6, 2023

Just as humans can learn through experience rather than merely following instructions, machines can learn by applying tools to data analysis. Machine learning works on a known problem with tools and techniques, creating algorithms that let a machine learn from data through experience and with minimal human intervention.

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Mlearning.ai

FEBRUARY 15, 2023

Introduction In natural language processing, text categorization tasks are common (NLP). Figure 4 Data Cleaning Conventional algorithms are often biased towards the dominant class, ignoring the data distribution. For many classification applications, random forest is now one of the best-performing algorithms.

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Pickl AI

JULY 14, 2023

Evolution of AI The evolution of Artificial Intelligence (AI) spans several decades and has witnessed significant advancements in theory, algorithms, and applications. Techniques such as decision trees, support vector machines, and neural networks gained popularity.

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Becoming Human

MARCH 16, 2023

AI began back in the 1950s as a simple series of “if, then rules” and made its way into healthcare two decades later after more complex algorithms were developed. Machine Learning Machine learning (ML) focuses on training computer algorithms to learn from data and improve their performance, without being explicitly programmed.

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Heartbeat

FEBRUARY 21, 2024

Deep learning uses deep (multilayer) neural networks to process large amounts of data and learn highly abstract patterns. This technology has achieved great success in many application areas, especially in image recognition, natural language processing, autonomous vehicles, voice recognition, and many more.

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IBM Journey to AI blog

AUGUST 28, 2023

One of the best ways to take advantage of social media data is to implement text-mining programs that streamline the process. Text representation In this stage, you’ll assign the data numerical values so it can be processed by machine learning (ML) algorithms, which will create a predictive model from the training inputs.

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Pickl AI

SEPTEMBER 12, 2024

A Algorithm: A set of rules or instructions for solving a problem or performing a task, often used in data processing and analysis. Decision Trees: A supervised learning algorithm that creates a tree-like model of decisions and their possible consequences, used for both classification and regression tasks.

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Pickl AI

SEPTEMBER 23, 2024

Understanding Data Science Data Science is a multidisciplinary field that uses scientific methods, algorithms, and systems to extract knowledge and insights from structured and unstructured data. Finance In finance, Data Science is critical in fraud detection, risk management, and algorithmic trading.

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Heartbeat

AUGUST 22, 2023

Introduction Text classification is the process of automatically assigning a set of predefined categories or labels to a piece of text. It’s an essential task in natural language processing (NLP) and machine learning, with applications ranging from sentiment analysis to spam detection. You can get the dataset here.

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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. Support Vector Machines In order to classify data more precisely, support vector machine methods create a partition (a hyperplane).

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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. Support Vector Machines In order to classify data more precisely, support vector machine methods create a partition (a hyperplane).

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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. To obtain practical expertise, run the algorithms on datasets. It can be easily ported to multiple platforms.

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