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Exploring the Viability of Generative Adversarial Networks for Audio Denoising

Exploring the Viability of Generative Adversarial Networks for Audio Denoising Sharing our experiences building an audio denoiser using GANs Photo by Jason Rosewell on Unsplash An article by Jacob Boness, Jamie Thomassen, and Colton Davenport One of the main goals of the Innovation team at Daitan is to keep our eyes open to emerging technology that can positively impact our clients. Undoubtedly, one of such technologies is...

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New electronic chip delivers smarter, light-powered AI

Researchers have developed artificial intelligence technology that brings together imaging, processing, machine learning and memory in one electronic chip, powered by light. The prototype shrinks artificial intelligence technology by imitating the way that the human brain processes visual information. The nanoscale advance combines the core software needed to drive artificial intelligence with image-capturing hardware in a single...

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Using generative models for explainable AI

Please find below the transcript for Season 2 Episode 5: Jeremie (00:00):Hello, and welcome to another episode of the Towards Data Science podcast. My name is Jeremie and I’m on the team over at the SharpestMinds data science mentorship program. Now, in the early 1900s a lot of our predictions were the direct product of the human brain. Scientists, analysts, climatologists, mathematicians, bankers, lawyers, politicians, they all...

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5 Machine Learning Projects for Healthcare

Electronically stored medical imaging data is plentiful and Machine Learning algorithms can be fed with this type of dataset, to detect and uncover patterns and anomalies. In this article, I will introduce you to five machine learning projects for healthcare. Machines and algorithms can interpret imaging data just as a highly trained radiologist could identify suspicious spots on the skin, lesions, tumours and bleeding in the...

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Introducing completely free datasets for data-driven deep reinforcement learning

Introducing completely free datasets for data-driven deep reinforcement learning In this blog post, I’m introducing the new datasets for data-driven deep reinforcement learning, which are available for completely free! What is data-driven deep reinforcement learning? Data-driven reinforcement learning (RL) is a paradigm that RL algorithms achieve policies to maximize rewards within the offline data, unlike online RL that...

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The future of Design and Artificial intelligence.

The future of Design and Artificial intelligence. Since the beginning of time designs have been manual, I mean artists had to take time, assemble all the required tool prepare scribes, papers and painting surfaces days before the actual date of doing the art. There’s no doubts that over the past hundred years the world of creatives and artists have experienced the influence of technology to how they work on their pieces of art....

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Big Things Are About To Happen: Google Releases Objectron Dataset

For evaluation of 3D object detection, we have the 3D counterpart of IoU (Intersection over Union) i.e. 3D IoU. This works by finding the intersection points of the 3D bounding boxes and then, using volume instead of area to do the calculation of IoU. The Areas That Will Be Disrupted Augmented Reality This is the field that will most benefit from this dataset. Datasets with indoor objects are less publicly available while most of...

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Big Things Are About To Happen: Google Releases Objectron Dataset

For evaluation of 3D object detection, we have the 3D counterpart of IoU (Intersection over Union) i.e. 3D IoU. This works by finding the intersection points of the 3D bounding boxes and then, using volume instead of area to do the calculation of IoU. The Areas That Will Be Disrupted Augmented Reality This is the field that will most benefit from this dataset. Datasets with indoor objects are less publicly available while most of...

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Fixing the Conflict between Math and Machine Learning

The evergreen question when someone into Machine learning is Do I need to know Math for Machine Learning? I suck at Math, can I able to pursue ML ( Machine Learning ) still? The blog is solemn of my takeaways and being practicing ML 6 months for now. So whatever is up to from now take it as a grain of salt, remember if it doesn’t work, you can always shift the boards and try another way. It all started with an Internship, I asked...

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Fixing the Conflict between Math and Machine Learning

The evergreen question when someone into Machine learning is Do I need to know Math for Machine Learning? I suck at Math, can I able to pursue ML ( Machine Learning ) still? The blog is solemn of my takeaways and being practicing ML 6 months for now. So whatever is up to from now take it as a grain of salt, remember if it doesn’t work, you can always shift the boards and try another way. It all started with an Internship, I asked...

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Dealing with the Incompleteness of Machine Learning

Dealing with the Incompleteness of Machine Learning The prospect of automating every aspect of human life is exciting. Imagine humans permanently living a life of leisure and machine learning robot labor picking up the slack! Even though this sounds like a recipe for lazy and depressed humans, we can still be useful to each other by building communities surrounded by interests and companionship. And gaining fulfillment that we...

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3 Must-Know Sorting Algorithms

Merge sort The merge sort algorithm is a little more complicated to grasp but it is more efficient than the previous two algorithms. It performs better in terms of time complexity. This algorithm has two parts. First part is the merge function that merges two sorted lists in a way that the resulting list is sorted. Please note that the lists must be sorted for the merge function to work. The merge function first compares the...

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How to Perform Fuzzy Dataframe Row Matching With RecordLinkage

Record Linkage, Case Study Now that you have an understanding of indexing, we can start record linkage with the full datasets: For full datasets, almost 5.5 million pairs are returned. Remember, if we used full indexing, it would have been 25 million. Now, using these candidate pairs, we will perform a comparison of each column value. To start comparing, we should create a comparing object: This object has many useful functions...

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Python影像辨識筆記(二十二):Scaled-YOLOv4: Scaling Cross Stage Partial Network相關連結與介紹

Python影像辨識筆記(二十二):Scaled-YOLOv4: Scaling Cross Stage Partial Network相關連結與介紹 論文連結 GitHub Repo 新增的功能 對比舊版的PyTorch_YOLOv4,這個版本的程式碼支援多GPU訓練、高Batch size訓練(batch = 64,每個epochs約15分鐘)、resume training 使用方法 以yolov4-csp branch在TWCC國網中心的主機為例: pip install...

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Decision Tree With Amazon Food Reviews

Decision Tree With Amazon Food Reviews Decision trees are a popular supervised learning method for a variety of reasons. The benefits of decision trees include that they can be used for both regression and classification, they are easy to interpret and they don’t require feature scaling. They have several flaws including being prone to overfitting. Contents What are Decision Trees?. Geometric Intuition of Decision...