Data Science Dojo

DECEMBER 28, 2023

That world is not science fiction—it’s the reality of machine learning (ML). In this blog post, we’ll break down the end-to-end ML process in business, guiding you through each stage with examples and insights that make it easy to grasp. Formatting the data in a way that ML algorithms can understand.

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Data Science Dojo

MAY 10, 2024

In this blog, we will focus on these embeddings in LLM and explore how they have evolved over time within the world of NLP, each transformation being a result of technological advancement and progress. The two main approaches of interest for embeddings include unsupervised and supervised learning.

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AWS Machine Learning Blog

JANUARY 31, 2025

This is a guest blog post co-written with Jordan Knight, Sara Reynolds, George Lee from Travelers. Increasingly, FMs are completing tasks that were previously solved by supervised learning, which is a subset of machine learning (ML) that involves training algorithms using a labeled dataset.

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Towards AI

SEPTEMBER 3, 2024

Let’s discuss two popular ML algorithms, KNNs and K-Means. They are both ML Algorithms, and we’ll explore them more in detail in a bit. K-Nearest Neighbors (KNN) is a supervised ML algorithm for classification and regression. This member-only story is on us. Upgrade to access all of Medium.

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Towards AI

JANUARY 11, 2024

In this article, I’ve covered one of the most famous classification and regression algorithms in machine learning, namely the Decision Tree. Image by Author There are other types of learning in Machine Learning, such as semi-supervised and… Read the full blog for free on Medium.

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Pickl AI

FEBRUARY 17, 2025

These figures underscore the pressing need for awareness and solutions regarding the challenges faced by Machine Learning professionals. Key Takeaways Data quality is crucial; poor data leads to unreliable Machine Learning models. Algorithmic bias can result in unfair outcomes, necessitating careful management.

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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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Data Science Dojo

JULY 2, 2024

In this blog, we will focus on one such developed aspect of AI called adaptive AI. It is a form of AI that learns, adapts, and improves as it encounters changes, both in data and the environment. Some key characteristics that make AI adaptive are: Ability to Learn Continuously The AI system can process and analyze new information.

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IBM Journey to AI blog

DECEMBER 19, 2023

In this blog we’ll go over how machine learning techniques, powered by artificial intelligence, are leveraged to detect anomalous behavior through three different anomaly detection methods: supervised anomaly detection, unsupervised anomaly detection and semi-supervised anomaly detection.

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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. Each algorithm is explained with its applications, strengths, and weaknesses, providing valuable insights for practitioners and enthusiasts in the field.

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Google Research AI blog

MARCH 6, 2023

First, there is a lack of scalability with conventional supervised learning approaches. In contrast, self-supervised learning can leverage audio-only data, which is available in much larger quantities across languages. This requires the learning algorithm to be flexible, efficient, and generalizable.

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AWS Machine Learning Blog

FEBRUARY 13, 2025

However, to demonstrate how this system works, we use an algorithm designed to reduce the dimensionality of the embeddings, t-distributed Stochastic Neighbor Embedding (t-SNE) , so that we can view them in two dimensions. This is the k-nearest neighbor (k-NN) algorithm. The following figure illustrates how this works.

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Explosion

APRIL 1, 2017

Prodigy features many of the ideas and solutions for data collection and supervised learning outlined in this blog post. It’s a cloud-free, downloadable tool and comes with powerful active learning models. Sometimes the unsupervised algorithm will happen to produce the output you want, but other times it won’t.

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AWS Machine Learning Blog

JULY 18, 2023

The built-in BlazingText algorithm offers optimized implementations of Word2vec and text classification algorithms. The BlazingText algorithm expects a single preprocessed text file with space-separated tokens. Set the learning mode hyperparameter to supervised. For instructions, see Create your first S3 bucket.

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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

AUGUST 28, 2024

Summary: This comprehensive guide covers the basics of classification algorithms, key techniques like Logistic Regression and SVM, and advanced topics such as handling imbalanced datasets. It also includes practical implementation steps and discusses the future of classification in Machine Learning. What is Classification?

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Data Science Dojo

SEPTEMBER 11, 2023

These complex algorithms are the backbone upon which our modern technological advancements rest and which are doing wonders for natural language communication. PaLM 2 stands for “ Progressive and Adaptive Language Model 2 ” and Llama 2 is short for “ Language Learning and Mastery Algorithm 2 ”.

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Pickl AI

FEBRUARY 2, 2025

This blog aims to explain associative classification in data mining, its applications, and its role in various industries. Classification: How it Differs from Association Rules Classification is a supervised learning technique that aims to predict a target or class label based on input features.

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AWS Machine Learning Blog

JANUARY 31, 2025

These models are trained using self-supervised learning algorithms on expansive datasets, enabling them to capture a comprehensive repertoire of visual representations and patterns inherent within pathology images.

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Pickl AI

JUNE 2, 2023

One of the most popular algorithms in Machine Learning are the Decision Trees that are useful in regression and classification tasks. Decision trees are easy to understand, and implement therefore, making them ideal for beginners who want to explore the field of Machine Learning. What is Decision Tree in Machine Learning?

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AWS Machine Learning Blog

DECEMBER 7, 2023

Amazon Forecast is a fully managed service that uses machine learning (ML) algorithms to deliver highly accurate time series forecasts. Calculating courier requirements The first step is to estimate hourly demand for each warehouse, as explained in the Algorithm selection section.

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AWS Machine Learning Blog

MAY 8, 2024

Amazon SageMaker JumpStart provides a suite of built-in algorithms , pre-trained models , and pre-built solution templates to help data scientists and machine learning (ML) practitioners get started on training and deploying ML models quickly. You can use these algorithms and models for both supervised and unsupervised learning.

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Towards AI

APRIL 18, 2023

This powerful self-supervised learning method is poised to transform the way businesses use computer vision in various applications, from e-commerce to manufacturing and beyond. In this blog post, we’ll explore what DINOv2 is, how it works, and the exciting possibilities it opens up for businesses.

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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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BAIR

APRIL 20, 2022

A demonstration of the RvS policy we learn with just supervised learning and a depth-two MLP. It uses no TD learning, advantage reweighting, or Transformers! Offline reinforcement learning (RL) is conventionally approached using value-based methods based on temporal difference (TD) learning.

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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

NOVEMBER 13, 2024

The answer lies in the various types of Machine Learning, each with its unique approach and application. In this blog, we will explore the four primary types of Machine Learning: Supervised Learning, UnSupervised Learning, semi-Supervised Learning, and Reinforcement Learning.

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Pickl AI

JULY 17, 2023

Machine Learning is a subset of artificial intelligence (AI) that focuses on developing models and algorithms that train the machine to think and work like a human. There are two types of Machine Learning techniques, including supervised and unsupervised learning.

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BAIR

APRIL 6, 2023

The closest analogue in academia is interactive imitation learning (IIL) , a paradigm in which a robot intermittently cedes control to a human supervisor and learns from these interventions over time. Using this formalism, we can now instantiate and compare IFL algorithms (i.e., allocation policies) in a principled way.

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IBM Journey to AI blog

JULY 6, 2023

To keep up with the pace of consumer expectations, companies are relying more heavily on machine learning algorithms to make things easier. This blog post will clarify some of the ambiguity. How do artificial intelligence, machine learning, deep learning and neural networks relate to each other?

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Hacker News

MAY 3, 2023

With these fairly complex algorithms often being described as “giant black boxes” in news and media, a demand for clear and accessible resources is surging. Fine-tuning may involve further training the pre-trained model on a smaller, task-specific labeled dataset, using supervised learning.

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IBM Journey to AI blog

MAY 9, 2023

The emergence of transformers and self-supervised learning methods has allowed us to tap into vast quantities of unlabeled data, paving the way for large pre-trained models, sometimes called “ foundation models.” Learn more about watsonx.ai But this is starting to change.

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Pickl AI

AUGUST 6, 2023

It includes supervised and unsupervised learning. Supervised Learning deals with labels data and unsupervised learning deals with unlabelled data. Supervised learning can be classified into classification and regression where regression deals with continuous values and the former deals with discrete values.

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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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Data Science Dojo

JUNE 11, 2024

They are capable of learning and improving over time as they are exposed to more data. Hence, solving a wide array of complex and high-dimensional problems unlike traditional algorithms. In this blog, we will discuss the 14 major types of neural networks that are put to practical use across industries.

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AWS Machine Learning Blog

MAY 30, 2023

Amazon SageMaker provides a suite of built-in algorithms , pre-trained models , and pre-built solution templates to help data scientists and machine learning (ML) practitioners get started on training and deploying ML models quickly. You can use these algorithms and models for both supervised and unsupervised learning.

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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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