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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The MLOps Blog

DECEMBER 19, 2022

Traditional Machine Learning and Deep Learning methods are used to solve Multiclass Classification problems, but the model’s complexity increases as the number of classes increases. Particularly in Deep Learning, the network size increases as the number of classes increases. Let’s take a look at some of them.

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PyImageSearch

JUNE 19, 2023

Each service uses unique techniques and algorithms to analyze user data and provide recommendations that keep us returning for more. This is where machine learning, statistics, and algebra come into play. Precision@K Precision measures the efficiency of a machine learning algorithm.

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Pickl AI

JULY 26, 2023

Highly Flexible Neural Networks Deep neural networks with a large number of layers and parameters have the potential to memorize the training data, resulting in high variance. K-Nearest Neighbors with Small k I n the k-nearest neighbours algorithm, choosing a small value of k can lead to high variance.

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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. What is Unsupervised Machine Learning?

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Mlearning.ai

NOVEMBER 29, 2023

All the previously, recently, and currently collected data is used as input for time series forecasting where future trends, seasonal changes, irregularities, and such are elaborated based on complex math-driven algorithms. And with machine learning, time series forecasting becomes faster, more precise, and more efficient in the long run.

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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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ODSC - Open Data Science

JANUARY 5, 2024

Scikit-learn A machine learning powerhouse, Scikit-learn provides a vast collection of algorithms and tools, making it a go-to library for many data scientists. Scikit-learn is also open-source, which makes it a popular choice for both academic and commercial use. And did any of your favorites make it in?

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Mlearning.ai

MAY 23, 2023

An interdisciplinary field that constitutes various scientific processes, algorithms, tools, and machine learning techniques working to help find common patterns and gather sensible insights from the given raw input data using statistical and mathematical analysis is called Data Science. What is Data Science? Let us see some examples.

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Mlearning.ai

MAY 23, 2023

With the advancement of technology, machine learning, and computer vision techniques can be used to develop automated solutions for leaf disease detection. In this article, we will discuss the development of a Leaf Disease Detection Flask App that uses a deep learning model to automatically detect the presence of leaf diseases.

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Mlearning.ai

MAY 21, 2023

If you are interested in exploring machine learning and want to dive into practical implementation, working on machine learning projects with source code is an excellent way to start. These projects also enable you to grasp the practical aspects of solving real-world problems using machine-learning techniques.

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Mlearning.ai

FEBRUARY 15, 2023

Figure 4 Data Cleaning Conventional algorithms are often biased towards the dominant class, ignoring the data distribution. Figure 11 Model Architecture The algorithms and models used for the first three classifiers are essentially the same. K-Nearest Neighbou r: The k-Nearest Neighbor algorithm has a simple concept behind it.

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Snorkel AI

APRIL 11, 2023

The unprecedented amount of available data has been critical to many of deep learning’s recent successes, but this big data brings its own problems. Active learning is a really powerful data selection technique for reducing labeling costs. It’s computationally demanding, resource hungry, and often redundant.

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Snorkel AI

APRIL 11, 2023

The unprecedented amount of available data has been critical to many of deep learning’s recent successes, but this big data brings its own problems. Active learning is a really powerful data selection technique for reducing labeling costs. It’s computationally demanding, resource hungry, and often redundant.

K-nearest Neighbors 52

K-nearest Neighbors Clustering Deep Learning Deep Learning 52

Snorkel AI

APRIL 11, 2023

The unprecedented amount of available data has been critical to many of deep learning’s recent successes, but this big data brings its own problems. Active learning is a really powerful data selection technique for reducing labeling costs. It’s computationally demanding, resource hungry, and often redundant.

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Mlearning.ai

JUNE 6, 2023

In today’s blog, we will see some very interesting Python Machine Learning projects with source code. This list will consist of Machine learning projects, Deep Learning Projects, Computer Vision Projects , and all other types of interesting projects with source codes also provided. This is a simple project.

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Google Research AI blog

AUGUST 15, 2023

We developed the STUDY algorithm in partnership with Learning Ally , an educational nonprofit, aimed at promoting reading in dyslexic students, that provides audiobooks to students through a school-wide subscription program. We evaluate the model on the entire test set (all) as well as the novel and non-continuation splits.

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Google Research AI blog

NOVEMBER 28, 2022

Organizing Committee General Chairs includes: Sanmi Koyejo Program Chairs include: Alekh Agarwal Workshop Chairs include: Hanie Sedghi Tutorial Chairs include: Adji Bousso Dieng , Jessica Schrouff Affinity Workshop Chair: Adji Bousso Dieng , Jessica Schrouff Program Committee, Senior Area Chairs include: Corinna Cortes , Claudio Gentile , Mohammad (..)

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AWS Machine Learning Blog

FEBRUARY 10, 2023

We design a K-Nearest Neighbors (KNN) classifier to automatically identify these plays and send them for expert review. We design an algorithm that automatically identifies the ambiguity between these two classes as the overlapping region of the clusters. The results show that most of them were indeed labeled incorrectly.

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