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Deep Learning - Convolutional Neural Networks - nieriorefasow63 - 06-22-2024
![[Image: bd3748102781e8adf185867169b23fac.jpg]](https://i123.fastpic.org/big/2024/0622/ac/bd3748102781e8adf185867169b23fac.jpg)
Deep Learning - Convolutional Neural Networks
Published 6/2024
Created by Yasir Amir
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English | Duration: 10 Lectures ( 3h 40m ) | Size: 1.58 GB
Easier way to learn Convolutional Neural Networks with Python
What you'll learn:
Convolutional Neural Networks (Deep Learning)
Requirements:
Machine Learning, Python
Description:
The age of intelligent machines that can see is here! Harness the transformative power of artificial intelligence. Now, there's an easier way to learn Convolutional Neural Networks (ConvNets) with Python.In just a few short years, ConvNets have ignited a revolution in computer vision. They've propelled us beyond clunky algorithms, empowering technologies like self-driving cars, unlocking the mysteries hidden within medical imagery through automated analysis, and even achieving near-human accuracy in facial recognition. This course equips you with the skills to join this transformative field and be a part of developing the next generation of groundbreaking applications.By the end, you'll be able to:Explain ConvNets, their components (convolutional layers, pooling layers, activation functions), and their inner workings. Design and code ConvNets using popular deep learning library like TensorFlow.Critically analyze existing ConvNet designs and algorithms, identifying strengths and weaknesses for different tasks. This course is your launchpad! It equips you with the essential building blocks, the rocketship fuel, to propel yourself into the vast and ever-expanding universe of Artificial Intelligence and Machine Learning. Here, you'll gain the foundational skills to navigate this incredible frontier, but the journey doesn't stop here. Dive deeper, explore further, and keep learning. This course is just the beginning of your exciting exploration!
Who this course is for:
Artificial Intelligence Enthusiasts and (even Practitioners), Software Engineering students and professionals, Electrical Engineers,
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