Towards AI

MAY 1, 2024

In this piece, we shall look at tips and tricks on how to perform particular GIS machine learning algorithms regardless of your expertise in GIS, if you are a fresh beginner with no experience or a seasoned expert in geospatial machine learning. Load machine learning libraries. Decision Tree and R.

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Towards AI

APRIL 4, 2024

Created by the author with DALL E-3 Machine learning algorithms are the “cool kids” of the tech industry; everyone is talking about them as if they were the newest, greatest meme. Amidst the hoopla, do people actually understand what machine learning is, or are they just using the word as a text thread equivalent of emoticons?

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AWS Machine Learning Blog

SEPTEMBER 10, 2024

Table 2 and Figure 2 show performance results of PORPOISE and HEEC, which show that HEEC is the only algorithm that outperforms the results of the best-performing single modality by combining multiple modalities. This location can be visually highlighted on the histology slide to be presented to expert pathologists for verification.

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DrivenData Labs

JUNE 14, 2023

Accurate and performant algorithms are critical in flagging and removing inappropriate content. Self-supervision: As in the Image Similarity Challenge , all winning solutions used self-supervised learning and image augmentation (or models trained using these techniques) as the backbone of their solutions.

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IBM Journey to AI blog

JULY 6, 2023

These computer science terms are often used interchangeably, but what differences make each a unique technology? To keep up with the pace of consumer expectations, companies are relying more heavily on machine learning algorithms to make things easier. Technology is becoming more embedded in our daily lives by the minute.

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Dataconomy

APRIL 3, 2023

Artificial intelligence, commonly referred to as AI , is the field of computer science that focuses on the development of intelligent machines that can perform tasks that would typically require human intervention. ML models are designed to learn from data and make predictions or decisions based on that data.

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Dataconomy

APRIL 3, 2023

Artificial intelligence, commonly referred to as AI , is the field of computer science that focuses on the development of intelligent machines that can perform tasks that would typically require human intervention. ML models are designed to learn from data and make predictions or decisions based on that data.

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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. Since the advent of deep learning in the 2000s, AI applications in healthcare have expanded. A few AI technologies are empowering drug design.

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Snorkel AI

OCTOBER 31, 2023

The Snorkel papers cover a broad range of topics including fairness, semi-supervised learning, large language models (LLMs), and domain-specific models. This paper explores fairness in weak supervision and presents an empirically validated model of fairness that captures labeling function bias.

Supervised Learning 59

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ODSC - Open Data Science

SEPTEMBER 19, 2023

Then identifying issues that allow fine-tuning of code, optimizing algorithms, and making strategic use of parallel processing. Depending on the position, and company, it can require a strong understanding of natural language processing, computer science, linguistics, and software engineering.

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Dataconomy

MARCH 13, 2023

Key concepts of AI The following are some of the key concepts of AI: Data:  AI requires vast amounts of data to learn and improve its performance over time. Algorithms:  AI algorithms are used to process the data and extract insights from it. Develop AI models using machine learning or deep learning 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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Dataconomy

MARCH 14, 2023

One major issue with conventional supervised learning approaches is that they lack scalability. On the other hand, self-supervised learning can utilize audio-only data, which is more readily available across a wide range of languages. This necessitates a flexible, efficient, and generalizable learning algorithm.

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Applied Data Science

MARCH 11, 2022

Then, we will look at three recent research projects that gamified existing algorithms by converting them from single-agent to multi-agent: ?️‍♀️ Our internal agents are playing games until they learn how to cooperate and trick us into believing we are an individual. All the rage was about algorithms for classification.

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Snorkel AI

OCTOBER 31, 2023

The Snorkel papers cover a broad range of topics including fairness, semi-supervised learning, large language models (LLMs), and domain-specific models. This paper explores fairness in weak supervision and presents an empirically validated model of fairness that captures labeling function bias.

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How to Learn Machine Learning

MAY 14, 2023

Building a Solid Foundation in Mathematics and Programming To become a successful machine learning engineer, it’s essential to have a strong foundation in mathematics and programming. Mathematics is crucial because machine learning algorithms are built on concepts such as linear algebra, calculus, probability, and statistics.

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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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Hacker News

MARCH 25, 2022

Transformers made self-supervised learning possible, and AI jumped to warp speed,” said NVIDIA founder and CEO Jensen Huang in his keynote address this week at GTC. Transformers are in many cases replacing convolutional and recurrent neural networks (CNNs and RNNs), the most popular types of deep learning models just five years ago.

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AWS Machine Learning Blog

SEPTEMBER 8, 2023

Image processing and anomaly detection pipeline The following figure demonstrates the detailed overview of our proposed approach that includes the data processing pipeline and various ML algorithms employed for anomaly detection. Precision measures how well our algorithm identifies only anomalies. Having received his B.S.

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PyImageSearch

SEPTEMBER 16, 2024

Home Table of Contents Credit Card Fraud Detection Using Spectral Clustering Understanding Anomaly Detection: Concepts, Types and Algorithms What Is Anomaly Detection? Jump Right To The Downloads Section Understanding Anomaly Detection: Concepts, Types, and Algorithms What Is Anomaly Detection? Looking for the source code to this post?

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Heartbeat

OCTOBER 25, 2023

Empowering Data Scientists and Machine Learning Engineers in Advancing Biological Research Image from European Bioinformatics Institute Introduction: In biological research, the fusion of biology, computer science, and statistics has given birth to an exciting field called bioinformatics.

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Pickl AI

JULY 10, 2024

Understanding AI and Machine Learning Artificial Intelligence (AI) is the simulation of human intelligence in machines designed to think and act like humans. AI encompasses various technologies and applications, from simple algorithms to complex neural networks. Hands-on projects in AI, including games and NLP tasks.

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AssemblyAI

NOVEMBER 21, 2022

Finding efficient and fast matrix multiplication algorithms is therefore paramount given that they will supercharge every neural network, potentially allowing us to run models prohibited by our current hardware limitations. Recently, DeepMind devised a method to automatically discover new faster matrix multiplication algorithms.

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Pickl AI

DECEMBER 3, 2024

It provides high-quality, curated data, often with associated tasks and domain-specific challenges, which helps bridge the gap between theoretical ML algorithms and real-world problem-solving. It is a goldmine for students, researchers, and industry professionals, who use it to develop models, benchmark new algorithms, and test hypotheses.

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Pickl AI

SEPTEMBER 12, 2024

Basic Data Science Terms Familiarity with key concepts also fosters confidence when presenting findings to stakeholders. Below is an alphabetical list of essential Data Science terms that every Data Analyst should know. Inductive Learning: A type of learning where a model generalises from specific examples to broader rules or patterns.

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Pickl AI

SEPTEMBER 18, 2024

Summary: Machine Learning Engineer design algorithms and models to enable systems to learn from data. Introduction Machine Learning is rapidly transforming industries. A Machine Learning Engineer plays a crucial role in this landscape, designing and implementing algorithms that drive innovation and efficiency.

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Snorkel AI

MARCH 1, 2023

Foundation models are large AI models trained on enormous quantities of unlabeled data—usually through self-supervised learning. What is self-supervised learning? Self-supervised learning is a kind of machine learning that creates labels directly from the input data. Find out in the guide below.

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ODSC - Open Data Science

FEBRUARY 14, 2023

The model was fine-tuned to reduce false, harmful, or biased output using a combination of supervised learning in conjunction to what OpenAI calls Reinforcement Learning with Human Feedback (RLHF), where humans rank potential outputs and a reinforcement learning algorithm rewards the model for generating outputs like those that rank highly.

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Pickl AI

AUGUST 1, 2024

This blog covers their job roles, essential tools and frameworks, diverse applications, challenges faced in the field, and future directions, highlighting their critical contributions to the advancement of Artificial Intelligence and machine learning. Insufficient or low-quality data can lead to poor model performance and overfitting.

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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. Data Science helps organisations make informed decisions by transforming raw data into valuable information.

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Pickl AI

JANUARY 12, 2023

This Data Science professional certificate program is industry-recognized and incorporates all the fundamentals of Data Science along with Machine Learning and its practical applications. The Udacity’s Data Science and Machine Learning course covers a wide range of topics in Data Science and Machine Learning.

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Hacker News

FEBRUARY 14, 2023

And many of the practical challenges around neural nets—and machine learning in general—center on acquiring or preparing the necessary training data. In many cases (“supervised learning”) one wants to get explicit examples of inputs and the outputs one is expecting from them. But that’s not the case.

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Pickl AI

APRIL 10, 2023

With the growing proliferation and impact of data-driven decisions on different industries, having expertise in the Data Science domain will always have a positive impact. Student Go for Data Science Course? Yes, BSE students can opt for Data Science courses. Is Data Science for Working Professionals a Good Option?

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DrivenData Labs

FEBRUARY 3, 2025

Recently, I became interested in machine learning, so I was enrolled in the Yandex School of Data Analysis and Computer Science Center. Machine learning is my passion and I often participate in competitions. The semi-supervised learning was repeated using the gemma2-9b model as the soft labeling model.

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Machine Learning (Theory)

APRIL 23, 2021

Welcome to ALT Highlights, a series of blog posts spotlighting various happenings at the recent conference ALT 2021 , including plenary talks, tutorials, trends in learning theory, and more! To reach a broad audience, the series will be disseminated as guest posts on different blogs in machine learning and theoretical computer science.

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Pickl AI

APRIL 2, 2024

Data science is the process of extracting the valuable minerals – the insights – that can transform your business. It’s a blend of statistics, computer science, and domain knowledge used to extract knowledge and create solutions from data. Data science for business leaders isn’t about becoming a coding pro.

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Dataconomy

MARCH 12, 2025

Machine teaching is redefining how we interact with artificial intelligence (AI) and machine learning (ML). As industries increasingly adopt AI solutions, professionals without a technical background can now step into the realm of machine learning, leveraging powerful algorithms to automate tasks and improve decision-making.

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