Tag: DL (Deep Learning)

Explainable AI is possible

Elena Daehnhardt · 21 Feb, 2024

The complexity of AI, particularly deep learning models, has led to the "black box" criticism, highlighting the lack of understanding about how deep learning models arrive at their decisions. While there's truth to this concern, having a nuanced view is important. In this post, I share my view on AI explainability, that it is complex, however possible. Read more...

Generate Music with AI

Elena Daehnhardt · 24 Aug, 2023

In this post, we will get into music generation with AI. We will briefly explore existing AI applications generating audio. We will explore transformer usage while coding music generation with HuggingFace transformers in Python. Read more...

Python coding with chatGPT

Elena Daehnhardt · 2 Jan, 2023

In this post, I did some Python coding with chatGPT. We have coded a neuron, a simple neural network, and learned how to train it. I am pleased with the result. I think that chatGPT has excellent potential for CS students and all coders that want to update their skills effectively. Is it an end of the StackOverflow? We cannot see the future. However, we still need social interaction with humans, and AI cannot substitute human communication. Read more...

TensorFlow: Transfer Learning (Feature Extraction) in Image Classification

Elena Daehnhardt · 3 Mar, 2022

Image classification is a complex task. However, we can approach the problem while reusing state-of-the-art pre-trained models. Using previously learned patterns from other models is named "Transfer Learning." This way, we can efficiently apply well-tested models, potentially leading to excellent performance. Read more...

TensorFlow: Convolutional Neural Networks for Image Classification

Elena Daehnhardt · 19 Feb, 2022

In this post, I have demonstrated CNN usage for birds recognition using TensorFlow and Kaggle 400 birds species dataset. We observed how the model works with the original and augmented images. Read more...

Artificial Neural Networks

Elena Daehnhardt · 17 Dec, 2021

Artificial neural networks (ANNs) are the cornerstone of Deep Learning algorithms. The name and the architecture are adopted from the human brain's neural network. ANNs are designed to simulate human reasoning based on how neurons communicate. ANNs contain a set of artificial neurons connected. Read more...

Deep Learning with DataCamp and Twitter

Elena Daehnhardt · 13 Dec, 2021

While having some machine learning experience of working with Scikit Learn, I was always interested in Deep Learning. The plan is to learn basic concepts and apply algorithms to a real-life situation, which I have always liked. Read more...

Deep Learning vs Machine Learning

Elena Daehnhardt · 16 Oct, 2021

Artificial Intelligence (AI) is a field of computer science. AI provides methods and algorithms to mimic human intelligence, reasoning, and decision-making and provide insights, which businesses could use in research or industry to build new exciting and innovative products or services. Machine Learning (ML) is a subset of AI with algorithms that learn from data. In this post, we sort out the differences between AI and ML. Read more...

Explainable AI is possible Elena Daehnhardt · 21 Feb, 2024 The complexity of AI, particularly deep learning models, has led to the "black box" criticism, highlighting the lack of understanding about how deep learning models arrive at their decisions. While there's truth to this concern, having a nuanced view is important. In this post, I share my view on AI explainability, that it is complex, however possible. Read more...
Generate Music with AI Elena Daehnhardt · 24 Aug, 2023 In this post, we will get into music generation with AI. We will briefly explore existing AI applications generating audio. We will explore transformer usage while coding music generation with HuggingFace transformers in Python. Read more...
Python coding with chatGPT Elena Daehnhardt · 2 Jan, 2023 In this post, I did some Python coding with chatGPT. We have coded a neuron, a simple neural network, and learned how to train it. I am pleased with the result. I think that chatGPT has excellent potential for CS students and all coders that want to update their skills effectively. Is it an end of the StackOverflow? We cannot see the future. However, we still need social interaction with humans, and AI cannot substitute human communication. Read more...
TensorFlow: Transfer Learning (Feature Extraction) in Image Classification Elena Daehnhardt · 3 Mar, 2022 Image classification is a complex task. However, we can approach the problem while reusing state-of-the-art pre-trained models. Using previously learned patterns from other models is named "Transfer Learning." This way, we can efficiently apply well-tested models, potentially leading to excellent performance. Read more...
TensorFlow: Convolutional Neural Networks for Image Classification Elena Daehnhardt · 19 Feb, 2022 In this post, I have demonstrated CNN usage for birds recognition using TensorFlow and Kaggle 400 birds species dataset. We observed how the model works with the original and augmented images. Read more...
Artificial Neural Networks Elena Daehnhardt · 17 Dec, 2021 Artificial neural networks (ANNs) are the cornerstone of Deep Learning algorithms. The name and the architecture are adopted from the human brain's neural network. ANNs are designed to simulate human reasoning based on how neurons communicate. ANNs contain a set of artificial neurons connected. Read more...
Deep Learning with DataCamp and Twitter Elena Daehnhardt · 13 Dec, 2021 While having some machine learning experience of working with Scikit Learn, I was always interested in Deep Learning. The plan is to learn basic concepts and apply algorithms to a real-life situation, which I have always liked. Read more...
Deep Learning vs Machine Learning Elena Daehnhardt · 16 Oct, 2021 Artificial Intelligence (AI) is a field of computer science. AI provides methods and algorithms to mimic human intelligence, reasoning, and decision-making and provide insights, which businesses could use in research or industry to build new exciting and innovative products or services. Machine Learning (ML) is a subset of AI with algorithms that learn from data. In this post, we sort out the differences between AI and ML. Read more...