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Deep Learning for Image Classification in Python with CNN

ProjectPro

Machines learning algorithms on the other hand, while classifying images face these challenges, and Image Classification becomes an exciting problem for us to solve. This field was again popularised by the Imagenet Challenge- Imagenet is a huge database of labeled images, the dataset has now over a million images with thousands of labels.

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50 ML Projects To Strengthen Your Portfolio and Get You Hired

ProjectPro

Each project explores new machine learning algorithms, datasets, and business problems. You will have a strong foundation in machine learning and its ways by practicing all these machine learning projects. You will learn to implement unet++ models for image segmentation using PyTorch.

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Top 22 Data Science Applications That You Should Know

Knowledge Hut

The software includes data analysis and machine learning models that automatically recognize user characteristics and show them product preferences accordingly. Medical Image Analysis Data science applications in healthcare or Medical science have several uses. Analyzing medical images is one of them.

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AI in Drug Discovery and Repurposing: Benefits, Approaches, and Use Cases

AltexSoft

So, it comes as no surprise that all large biopharma companies are investing in AI, particularly in deep learning , which has the potential to make the hunt for drugs cheaper, faster, and more precise. It’s worth noting that regulatory bodies treat the use of machine learning in healthcare with caution. Source: Deloitte.

Medical 52
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15 Generative Adversarial Networks (GAN) Based Project Ideas

ProjectPro

For true labels, the Discriminator model uses the raw input images from the MNIST dataset. We recommend using Anime Face Dataset. The most popular GAN architecture used for this task is DCGAN or Deep Convolutional GAN. You can use the CelebFaces Attributes (CelebA) Dataset for training the model.

Project 52
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Data Science Learning Path [Beginners Roadmap]

Knowledge Hut

Understanding what defines data in the modern world is the first step toward the Data Science self-learning path. For example, you might be interested more in healthcare, where you get to deal with medical or clinical data. Data Science is an advanced skill, and it's important to know why you are learning it.

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A Collection of Take-Home Data Science Challenges for 2023

ProjectPro

With Bitcoin witnessing initial success, many investors consider cryptocurrency as an asset for their portfolio. One way to help the investors is to give them a fair idea of the risks involved by predicting the returns using machine learning.