ODSC - Open Data Science

MARCH 22, 2023

Be sure to check out his session, “ Improving ML Datasets with Cleanlab, a Standard Framework for Data-Centric AI ,” there! Anybody who has worked on a real-world ML project knows how messy data can be. Everybody knows you need to clean your data to get good ML performance. A common gripe I hear is: “Garbage in, garbage out.

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Data Science Dojo

JUNE 1, 2023

Machine Learning for Absolute Beginners by Kirill Eremenko and Hadelin de Ponteves This is another beginner-level course that teaches you the basics of machine learning using Python. The course covers topics such as supervised learning, unsupervised learning, and reinforcement learning.

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Dataversity

DECEMBER 16, 2022

2022 was a big year for AI, and we’ve seen significant advancements in various areas – including natural language processing (NLP), machine learning (ML), and deep learning. Unsupervised and self-supervised learning are making ML more accessible by lowering the training data requirements.

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Dataconomy

MARCH 27, 2023

However, while RPA and ML share some similarities, they differ in functionality, purpose, and the level of human intervention required. In this article, we will explore the similarities and differences between RPA and ML and examine their potential use cases in various industries. What is machine learning (ML)?

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Heartbeat

FEBRUARY 15, 2023

It is a supervised learning methodology that predicts if a piece of text belongs to one category or the other. As a machine learning engineer, you start with a labeled data set that has vast amounts of text that have already been categorized. plot(history) Make sure you log the training loss and accuracy metrics to Comet ML.

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phData

AUGUST 24, 2023

What Does a Credit Score or Decisioning ML Pipeline Look Like? Now that we have a firm grasp on the underlying business case, we will now define a machine learning pipeline in the context of credit models. Let’s take a brief look at the below image to see how Snowpark can be used for an end-to-end machine learning solution.

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PyImageSearch

MARCH 30, 2023

If you want a gentle introduction to machine learning for computer vision, you’re in the right spot. Here at PyImageSearch we’ve been helping people just like you master deep learning for computer vision. Also, you might want to check out our computer vision for deep learning program before you go.

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Dataconomy

MAY 4, 2023

Machine learning applications in healthcare are revolutionizing the way we approach disease prevention and treatment Machine learning is broadly classified into three categories: supervised learning, unsupervised learning, and reinforcement learning.

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Dataconomy

APRIL 18, 2023

Undetectable backdoors can be implemented in any ML algorithm Machine learning Machine learning is a subfield of artificial intelligence that focuses on the development of algorithms and models that can learn from data and make predictions or decisions.

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IBM Journey to AI blog

AUGUST 11, 2023

Machine learning (ML), a subset of artificial intelligence (AI), is an important piece of data-driven innovation. Machine learning engineers take massive datasets and use statistical methods to create algorithms that are trained to find patterns and uncover key insights in data mining projects. What is MLOps?

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AssemblyAI

SEPTEMBER 12, 2023

Though once the industry standard, accuracy of these classical models had plateaued in recent years, opening the door for new approaches powered by advanced Deep Learning technology that’s also been behind the progress in other fields such as self-driving cars. The data does not need to be force-aligned.

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Heartbeat

AUGUST 29, 2023

Deep learning is a branch of machine learning that makes use of neural networks with numerous layers to discover intricate data patterns. Deep learning models use artificial neural networks to learn from data. Semi-Supervised Learning : Training is done using both labeled and unlabeled data.

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Heartbeat

JULY 6, 2023

Object detection is typically achieved through the use of deep learning models, particularly Convolutional Neural Networks (CNNs). In this article, you will learn about object detection through the SWIN Transformer. What is the Swin Transformer? If you’d like to contribute, head on over to our call for contributors.

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Heartbeat

FEBRUARY 7, 2023

image by rawpixel.com Understanding the concept of language models in natural language processing (NLP) is very important to anyone working in the Deep learning and machine learning space. Learn more from Uber’s Olcay Cirit. One of the areas that has seen significant growth is language modeling.

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Mlearning.ai

JULY 6, 2023

NOTES, DEEP LEARNING, REMOTE SENSING, ADVANCED METHODS, SELF-SUPERVISED LEARNING A note of the paper I have read Photo by Kelly Sikkema on Unsplash Hi everyone, In today’s story, I would share notes I took from 32 pages of Wang et al., 2022 Deep learning notoriously needs a lot of data in training.

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Heartbeat

FEBRUARY 28, 2023

The past few years have witnessed exponential growth in medical image analysis using deep learning. In this article we will look into medical image segmentation and see how deep learning can be helpful in these cases. This can be further classified as supervised and unsupervised learning. Image by author.

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IBM Journey to AI blog

JULY 6, 2023

While artificial intelligence (AI), machine learning (ML), deep learning and neural networks are related technologies, the terms are often used interchangeably, which frequently leads to confusion about their differences. Machine learning is a subset of AI. This blog post will clarify some of the ambiguity.

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The MLOps Blog

FEBRUARY 22, 2024

At the beginning of my machine learning journey, I was convinced that creating an ML model always looks similar. But most real-world machine learning (ML) projects are not like that. These problems keep many ML practitioners awake at night. If you’re part of this group, continual learning is exactly what you need.

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Mlearning.ai

DECEMBER 13, 2023

Mastering Deep Learning and AI Interview Questions: What You Need to Know Image created by the author on Canva Knowledge is power, but enthusiasm pulls the switch.” Ever wondered what it takes to excel in deep learning interviews? Explain how you would implement transfer learning in a deep learning model.

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Mlearning.ai

JUNE 27, 2023

Supervised learning approaches, which rely on annotated data for training, demand a significant amount of human work to accurately categorize pictures. The sheer volume of data necessary to train deep learning models exacerbates the problem.

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Dataconomy

MAY 25, 2023

By leveraging techniques like machine learning and deep learning, IoT devices can identify trends, anomalies, and patterns within the data. Here are some important machine learning techniques used in IoT: Supervised learning Supervised learning involves training machine learning models with labeled datasets.

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AWS Machine Learning Blog

AUGUST 16, 2023

Training machine learning (ML) models to interpret this data, however, is bottlenecked by costly and time-consuming human annotation efforts. One way to overcome this challenge is through self-supervised learning (SSL). His specialty is Natural Language Processing (NLP) and is passionate about deep learning.

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IBM Journey to AI blog

JULY 6, 2023

What is machine learning? Machine learning (ML) is a subset of artificial intelligence (AI) that focuses on learning from what the data science comes up with. Some examples of data science use cases include: An international bank uses ML-powered credit risk models to deliver faster loans over a mobile app.

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Google Research AI blog

APRIL 30, 2023

Posted by Catherine Armato, Program Manager, Google The Eleventh International Conference on Learning Representations (ICLR 2023) is being held this week as a hybrid event in Kigali, Rwanda. We are proud to be a Diamond Sponsor of ICLR 2023, a premier conference on deep learning, where Google researchers contribute at all levels.

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AWS Machine Learning Blog

MARCH 6, 2024

Similarly, pLMs are pre-trained on large protein sequence databases using unlabeled, self-supervised learning. save_to_disk(test_s3_uri) Create a training script SageMaker script mode allows you to run your custom training code in optimized machine learning (ML) framework containers managed by AWS.

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Mlearning.ai

MARCH 7, 2023

Dive Into Deep Learning — Part 3 In this part, I will summarize section 3.6 Dive Into Deep Learning — Part 2 Dive Into Deep Learning — Part1 Generalization The authors give an example of students who prepare for an exam, student 1 memorizes the past exams questions and student 2 discovers patterns in the questions, if the exam is 1.

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KDnuggets

DECEMBER 16, 2019

It is an annual tradition for Xavier Amatriain to write a year-end retrospective of advances in AI/ML, and this year is no different. Gain an understanding of the important developments of the past year, as well as insights into what expect in 2020.

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Heartbeat

OCTOBER 25, 2023

Machine Learning Tools in Bioinformatics Machine learning is vital in bioinformatics, providing data scientists and machine learning engineers with powerful tools to extract knowledge from biological data. Deep learning, a subset of machine learning, has revolutionized image analysis in bioinformatics.

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Mlearning.ai

NOVEMBER 29, 2023

How to Use Machine Learning (ML) for Time Series Forecasting — NIX United The modern market pace calls for a respective competitive edge. Data forecasting has come a long way since formidable data processing-boosting technologies such as machine learning were introduced.

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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. However, the growing influence of ML isn’t without complications.

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Heartbeat

JULY 20, 2023

Limited availability of labeled datasets: In some domains, there is a scarcity of datasets with fine-grained annotations, making it difficult to train segmentation networks using supervised learning algorithms. We’re committed to supporting and inspiring developers and engineers from all walks of life.

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Mlearning.ai

JUNE 1, 2023

Using PyTorch Deep Learning Framework and CNN Architecture Photo by Andrew S on Unsplash Motivation Build a proof-of-concept for Audio Classification using a deep-learning neural network with PyTorch framework. This is inherently a supervised learning problem. Data Source here.

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Dataconomy

MARCH 14, 2023

This was a significant pledge to construct a machine learning (ML) model that would facilitate the usage of the world’s one thousand most commonly spoken languages, promoting inclusion and accessibility for billions of people worldwide. The Conformer, or convolution-augmented transformer, is used as the encoder in USM.

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Google Research AI blog

MARCH 28, 2023

Posted by Harsh Mehta, Software Engineer, and Walid Krichene, Research Scientist, Google Research Large deep learning models are becoming the workhorse of a variety of critical machine learning (ML) tasks.

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Snorkel AI

FEBRUARY 6, 2023

You could imagine, for deep learning, you need, really, a lot of examples. So, deep learning, similarity search is a very easy, simple, task. And that’s the power of self-supervised learning. But desert, ocean, desert, in this way, I think that’s what the power of self-supervised learning is.

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Snorkel AI

FEBRUARY 6, 2023

You could imagine, for deep learning, you need, really, a lot of examples. So, deep learning, similarity search is a very easy, simple, task. And that’s the power of self-supervised learning. But desert, ocean, desert, in this way, I think that’s what the power of self-supervised learning is.

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Heartbeat

SEPTEMBER 20, 2023

Deep learning-based models, especially CNNs, have revolutionized feature extraction in image captioning. CNNs are particularly well-suited for this task due to their ability to learn hierarchical representations of visual data. In image captioning, a pre-trained CNN is often utilized to extract image features.

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