Remove 2001 Remove Datasets Remove Deep Learning
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Seeing the Forest for the Trees by James Strong

Scott Logic

I recently embarked on a journey into the world of machine learning through following the fast.ai I have learnt a great deal about the inner workings of neural networks and how deep learning can produce seemingly magical results. Most often, the goal is to predict a target feature of the dataset based on the rest.

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100+ Machine Learning Datasets Curated For You

ProjectPro

Undoubtedly, everyone knows that the only best way to learn data science and machine learning is to learn them by doing diverse projects. Table of Contents What is a dataset in machine learning? Why you need machine learning datasets? Where can I find datasets for machine learning?

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Facial Emotion Recognition Project using CNN with Source Code

ProjectPro

In 2001, researchers from Microsoft gave us face detection technology which is still used in many forms. With modern deep learning techniques, we have advanced to detect difficult things like smiles, eyes, and emotions. Before we jump on to the code, allow us to give you a fair idea of the dataset.

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A Collection of Take-Home Data Science Challenges for 2023

ProjectPro

By implementing various machine learning algorithms over a dataset of dates, store, item information, promotions, and unit sales, you will be using time forecasting methods to predict the sales. This challenge is about implementing deep learning object detection models over the thousands of images collected by the underwater camera.

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A State-of-the-Art Method for Generating Photo-Realistic Textures in Real Time

Zalando Engineering

2017] ) papers at world-class machine learning conferences, and the source code ( SGAN and PSGAN ) to reproduce the research is also available on GitHub. State-of-the-art in Machine Learning It’s all over town. Machine learning, and in particular deep learning, is the new black. 2016] and [Bergmann et al.

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Computer Vision: Algorithms and Applications to Explore in 2023

ProjectPro

With the advancement in artificial intelligence and machine learning and the improvement in deep learning and neural networks, Computer vision algorithms can process massive volumes of visual data. This algorithm is slow to train for a given dataset but can detect faces with impressive speed and accuracy in real-time.