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Deep Learning (DL) has attracted much interest in a wide range of applications such as image recognition, speech recognition and artificial intelligence, both from academia and industry. This lecture introduces the core elements of neural networks and deep learning, it comprises: (multilayer) perceptron, backpropagation, fully connected neural networks loss functions and optimization strategies convolutional neural networks (CNNs) activation functions regularization strategies common practic ...
 
Find me on Github/Twitter/Kaggle @SamDeepLearning. Find me on LinkedIn @SamPutnam. This Podcast is supported by Enterprise Deep Learning | Cambridge/Boston | New York City | Hanover, NH | http://www.EnterpriseDeepLearning.com. Contact: Sam@EDeepLearning.com, 802-299-1240, P.O. Box 863, Hanover, NH, USA, 03755. We move deep learning to production. I teach the worldwide Deploying Deep Learning Masterclass at http://www.DeepLearningConf.com in NYC regularly and am a Deep Learning Consultant ser ...
 
Most AI research today is done by elite universities and corporate labs. The pursuit of science and creativity should be a viable project for any person, from any walk of life, who is excited by that feeling of mystery and building something that grows. chloe is an end to end neural network chatbot written in PyTorch based on the transformer. Accomplishing goals through conversation is a task we can relate to, chatbots are an ideal agent through which to connect new research to our current u ...
 
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Firas is the Co-Founder of Volkswagens AG AI Team and Head of Deep Learning at the Expert Centre in Munich. A gentlemen who has dedicated his life to Data and AI. Firas has worked for multiple big players in the industry such as Audi, DLR & now Volkswagen. Today we get to learn from Firas's perspective on the current state of AI, effectively buildi…
 
Alexey Grigorev is a Principle Data Scientist at OLX Group and founder of DataTalks.Club with the vision to be the go to community for everything data. Alexey is a true expert and today he channels his knowledge into topics around the booming area of MLOps. Alexey shares advice for young and aspiring Data Scientists and we will also find out what h…
 
Ritesh Kanjee is a computer vision expert who has channelled his skillset into training and mentoring which led him to create Augmented Startups. Ritesh prides himself in being a Computer Vision and AI content creator and has amassed nearly 100,000 subscribers on YouTube. His company, Augmented Startups are at the forefront of Artificial Intelligen…
 
In todays episode I will be speaking with Nikolaas Steenbergen, Co-Founder of 030Solutions. A brand new start-up based in Berlin which uses laser and image data from mobile mapping vehicles or drones, using a smart AI software to survey, record and analyze data for mapping distributed infrastructure such as electricity distribution networks. Nikola…
 
Information is readily available, but so is misinformation. Don't believe everything you see on your screen. Actively resist your native confirmation bias that shops for prepackaged opinions that square with your preconceptions/tribe. Learning requires intellectual humility that assumes a willingness to be taught.…
 
In this episode I will be speaking with Leon Szeli, CEO and Co-Founder of Presize, an exciting Start-up in Munich which has already created huge waves in the eCommerce and AI world. I will be getting to know Leon and how his progressed so quickly but effectively in the last 2 years. We will be covering his unique product in the field of computer vi…
 
I am very excited to announce the 1st episode of The Deep Learning Crowd Podcast - where I speak to Dr. Holger Bartel, CEO & Founder of RealRate In this episode, we get to know Holger and what RealRate do in the world of AI. We break down XAI and the concerns we are facing, also understanding Hybrid AI and the importance of it. Lastly we dive into …
 
Justin Johnson, now at Facebook, wrote the original Torch implementation of the Gatys 2015 paper, which combines the content of one image and the style of another image using convolutional neural networks. Manuel Ruder’s newer 2016 paper transfers the style of one image to a whole video sequence, and it uses a computer vision technique called optic…
 
I talk through generating 10 melodies, two of which I play at the conclusion using a model trained on thousands of midi examples contained in a .mag Magenta file bundle. I used the Biaxial RNN (https://github.com/hexahedria/biaxial-rnn-music-composition) by a student named Daniel Johnson and the Basic RNN (https://github.com/tensorflow/magenta/tree…
 
I talk through generating an image of IRS tax return characters using a model trained on the IRS tax return dataset - NMIST. The authors trained for 70 hours on 32 GPUs. I used unconditioned image generation to create an image in 6 hours on my MacBook Pro CPU. I used the TensorFlow implementation of Conditional Image Generation with PixelCNN Decode…
 
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