Heartbeat

FEBRUARY 21, 2024

Photo by Almos Bechtold on Unsplash Deep learning is a machine learning sub-branch that can automatically learn and understand complex tasks using artificial neural networks. Deep learning uses deep (multilayer) neural networks to process large amounts of data and learn highly abstract patterns.

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Heartbeat

AUGUST 1, 2023

A World of Computer Vision Outside of Deep Learning Photo by Museums Victoria on Unsplash IBM defines computer vision as “a field of artificial intelligence (AI) that enables computers and systems to derive meaningful information from digital images, videos and other visual inputs [1].”

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Data Science Dojo

SEPTEMBER 8, 2023

We’ll dive into the core concepts of AI, with a special focus on Machine Learning and Deep Learning, highlighting their essential distinctions. Descriptive analytics involves summarizing historical data to extract insights into past events. Goals To predict future events and trends.

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Heartbeat

NOVEMBER 14, 2023

For many years, gradient-boosting models and deep-learning solutions have won the lion's share of Kaggle competitions. XGBoost is not limited to machine learning tasks, as its incredible power can be harnessed when harmonized with deep learning algorithms. 2 (2021): 522–531.

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Heartbeat

NOVEMBER 21, 2023

Computer vision, the field dedicated to enabling machines to perceive and understand visual data, has witnessed a monumental shift in recent years with the advent of deep learning. Photo by charlesdeluvio on Unsplash Welcome to a journey through the advancements and applications of deep learning in computer vision.

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Heartbeat

OCTOBER 18, 2023

In this article, we embark on a journey to explore the transformative potential of deep learning in revolutionizing recommender systems. However, deep learning has opened new horizons, allowing recommendation engines to unravel intricate patterns, uncover latent preferences, and provide accurate suggestions at scale.

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ODSC - Open Data Science

OCTOBER 17, 2023

But without a strong understanding of deep learning, you’ll have a difficult time getting the most out of the cutting-edge developments in the industry. At ODSC West this October 30th to November 2nd, you’ll build the core knowledge and skills you need with the sessions in the deep learning track , such as the ones listed below.

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Heartbeat

NOVEMBER 27, 2023

Deep learning automates and improves medical picture analysis. Convolutional neural networks (CNNs) can learn complicated patterns and features from enormous datasets, emulating the human visual system. Convolutional Neural Networks (CNNs) Deep learning in medical image analysis relies on CNNs.

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Heartbeat

JUNE 23, 2023

However, with the advent of deep learning, researchers have explored various neural network architectures to model and forecast time series data. In this post, we will look at deep learning approaches for time series analysis and how they might be used in real-world applications. Let’s dive in!

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Smart Data Collective

AUGUST 26, 2021

Deep learning technology is changing the future of small businesses around the world. A growing number of small businesses are using deep learning technology to address some of their most pressing challenges. New advances in deep learning are integrated into various accounting algorithms.

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Heartbeat

APRIL 23, 2023

Photo by RetroSupply on Unsplash Introduction Deep learning has been widely used in various fields, such as computer vision, NLP, and robotics. The success of deep learning is largely due to its ability to learn complex representations from data using deep neural networks. What is Epistemic Uncertainty?

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Heartbeat

MAY 23, 2023

As technology continues to improve exponentially, deep learning has emerged as a critical tool for enabling machines to make decisions and predictions based on large volumes of data. Edge computing may change how we think about deep learning. Standardizing model management can be tricky but there is a solution.

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Heartbeat

FEBRUARY 6, 2023

How do Object Detection Algorithms Work? There are two main categories of object detection algorithms. Two-Stage Algorithms: Two-stage object detection algorithms consist of two different stages. Single-stage object detection algorithms do the whole process through a single neural network model.

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ODSC - Open Data Science

APRIL 18, 2023

In particular, finance has seen some of the strongest benefits from automation and analysis thanks to AI and machine learning. Now, we’d like to go a bit deeper and specifically examine the role of machine learning in algorithmic trading, including portfolio optimization and pattern recognition.

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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. Finally, we will look at some of the recent semi-supervised medical image segmentation algorithms.

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Data Science Dojo

SEPTEMBER 25, 2024

By leveraging AI-powered algorithms, media producers can improve production processes and enhance creativity. Some key benefits of integrating the production process with AI are as follows: Personalization AI algorithms can analyze user data to offer personalized recommendations for movies, TV shows, and music.

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Dataconomy

SEPTEMBER 25, 2024

AI integration in real-time data processing Artificial intelligence enhances real-time data processing through better comprehension with the help of advanced machine learning algorithms and analytics to act on that information. For instance, in financial markets, AI algorithms running on real-time data feed predict market fluctuations.

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Heartbeat

JULY 25, 2023

Introduction When it comes to practicing deep learning at home vs. industry, there’s a huge disconnect. Every course, tutorial, and YouTube video presents you with a nicely prepared dataset to feed any DL algorithm for any DL framework. And is that system in a completely different framework or programming language?

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ODSC - Open Data Science

JANUARY 27, 2023

Ten Game-Changing Generative AI Projects, The Quest for the Ultimate Learning Algorithm, and Training Your PyTorch Model Top Ten Game-Changing Generative AI Projects in 2023 Here are our picks for a few generative AI projects that are worth checking out for yourself, most of which you can experiment with for free. Get the deal here!

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Pickl AI

AUGUST 5, 2024

Introduction Deep Reinforcement Learning (DRL) is a rapidly advancing field that combines the power of Deep Learning with the principles of reinforcement learning. By the end of this blog post, you’ll have a better understanding of how DRL works and how you can start exploring this fascinating field.

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Heartbeat

MARCH 14, 2023

By incorporating computer vision methods and algorithms into robots, they are able to view and understand their environment. Object recognition and tracking algorithms include the CamShift algorithm , Kalman filter , and Particle filter , among others.

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ODSC - Open Data Science

SEPTEMBER 17, 2024

It is known for its simplicity and efficiency, which makes it a popular framework for beginners interested in machine learning. It provides a range of supervised and unsupervised learning algorithms, along with tools for model fitting, data preprocessing, and evaluation.

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Dataconomy

APRIL 16, 2024

These chips will be implemented across Meta’s data centers to support AI applications, notably enhancing deep learning recommendation systems that boost user engagement on its platforms. ” -Meta For instance, just last week, Google Cloud launched its inaugural Arm-based CPU during the Google Cloud Next 2024 event.

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DrivenData Labs

APRIL 10, 2024

In the Kelp Wanted challenge, participants were called upon to develop algorithms to help map and monitor kelp forests. Winning algorithms will not only advance scientific understanding, but also equip kelp forest managers and policymakers with vital tools to safeguard these vulnerable and vital ecosystems.

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AWS Machine Learning Blog

MAY 16, 2024

Therefore, we decided to introduce a deep learning-based recommendation algorithm that can identify not only linear relationships in the data, but also more complex relationships. Recommendation model using NCF NCF is an algorithm based on a paper presented at the International World Wide Web Conference in 2017.

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Smart Data Collective

JUNE 4, 2021

Data scientists use algorithms for creating data models. Probability is the measurement of the likelihood of events. Probability distributions are collections of all events and their probabilities. Whereas in machine learning, the algorithm understands the data and creates the logic. Semi-Supervised Learning.

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IBM Journey to AI blog

AUGUST 9, 2024

Most generative AI models start with a foundation model , a type of deep learning model that “learns” to generate statistically probable outputs when prompted. Predictive AI blends statistical analysis with machine learning algorithms to find data patterns and forecast future outcomes.

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Flipboard

JULY 1, 2023

In a paper presented earlier this year at the European Space Agency’s second NEO and Debris Detection Conference in Darmstadt, Germany, Fabrizio Piergentili and colleagues presented results of their evolutionary “genetic” algorithm to monitor the rotational motion of space debris.

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Heartbeat

JANUARY 15, 2024

The field of computer vision has brought us a step closer to this reality by developing sophisticated algorithms to extract meaningful information from visual data automatically. We will also compare their performance with the formidable deep learning-based segmentation techniques, bringing out the unique strengths of each approach.

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Flipboard

JULY 31, 2023

Importance and Role of Datasets in Machine Learning Data is king. Algorithms are important and require expert knowledge to develop and refine, but they would be useless without data. Datasets are to machine learning what fuel is to a car: they power the entire process. Object detection is useful for many applications (e.g.,

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Heartbeat

AUGUST 14, 2023

Expertise in image segmentation requires knowledge of various techniques, ranging from traditional methods, such as thresholding and edge-based segmentation, to more advanced techniques, like deep learning-based segmentation. CNNs can learn to segment images by training on large datasets of labeled images.

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Heartbeat

MARCH 8, 2023

To extract themes from a corpus of text data and then use these themes as features in text classification algorithms, topic modeling can be used in text classification. Based on the words in the email as characteristics, the algorithm determines the likelihood of each class (spam or non-spam). References Nagesh, Singh Chauhan.

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Applied Data Science

JANUARY 4, 2022

Trying to make a summary of what happened in the world of AI out of a long and vague chain of events? Reinforcement learning rethinking its practices ?‍? Four awkward moments for AI Packing a full year of exciting AI events into a single post is not easy. Hiding your 2021 resolution list under a glass of champagne?

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ODSC - Open Data Science

FEBRUARY 8, 2024

Deep Learning with PyTorch and TensorFlow Dr. Jon Krohn | Chief Data Scientist | Nebula.io Jon Krohn, for an immersive introduction to Deep Learning that brings high-level theory to life with interactive examples featuring all three of the principal Python libraries, PyTorch, TensorFlow 2, and Keras.

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ODSC - Open Data Science

FEBRUARY 9, 2024

Most coverage focuses on large language models (LLMs), which are deep learning frameworks trained on massive text samples to generate believable text output. Generative chemistry algorithms typically process database molecules or proteins with known properties such that they are represented as training data in graph form.

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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. NLP algorithms help computers understand, interpret, and generate natural language.

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Smart Data Collective

JUNE 22, 2023

Taking the world by storm, artificial intelligence and machine learning software are changing the landscape in many fields. Earlier today, one analysis found that the market size for deep learning was worth $51 billion in 2022 and it will grow to be worth $1.7 Amazon has a very good overview if you want to learn more.

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