📌11 Data Science careers shaping our future

1. Business Intelligence (BI) Developer
Average Salary: $89,333

2. Data Architect
Average Salary: $137,630

3. Applications Architect
Average Salary: $134,520

4. Infrastructure Architect
Average Salary: $126,353

5. Enterprise Architect
Average Salary: $161,272

6. Data Scientist
Average Salary: $139,840

7. Data Analyst
Average Salary: $83,878

8. Data Engineer
Average Salary: $151,307

9. Machine Learning Scientist
Average Salary: $139,840

10. Machine Learning Engineer
Average Salary: $114,826

11. Statistician
Average Salary: $93,589

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📌Via: @cedeeplerning
📌Social media: https://linktr.ee/cedeeplearning

link: https://www.northeastern.edu/graduate/blog/data-science-careers-shaping-our-future/

#machinelearning
#datascience
#deeplearning
#career
#salary

🔹Deep Learning 101 — Role of Deep Learning in Artificial Intelligence

While deep learning itself is a concept, neural networks are a model for deep learning. The architecture of a neural network is inspired by the way biological neurons interact with each other.

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📌Via: @cedeeplearning
📌Social media: https://linktr.ee/cedeeplearning

https://medium.com/senseai/deep-learning-101-role-of-deep-learning-in-artificial-intelligence-d949d0ffc4f6

#machinelearning
#deeplearning
#datascience
#neuralnetworks

📌Cheat Sheets for AI, Neural Networks, Machine Learning, Deep Learning & Big Data

🔻Do not miss out this amazing article🔻

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📌Via: @cedeeplearning

https://becominghuman.ai/cheat-sheets-for-ai-neural-networks-machine-learning-deep-learning-big-data-678c51b4b463

🔹Neural Networks and Modern BI Platforms Will Evolve Data and Analytics

🔻Gartner will help you to be more clear about the future of AI and Deep learning

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📌Via: @cedeeplearning

https://www.gartner.com/smarterwithgartner/nueral-networks-and-modern-bi-platforms-will-evolve-data-and-analytics/

🔻Deep learning AI discovers surprising new #antibiotics

Enter deep learning. These #algorithms power many of today’s facial recognition systems and #self_driving cars. They mimic how neurons in our brains operate by learning patterns in data. An individual artificial #neuron – like a mini sensor – might detect simple patterns like lines or circles. By using thousands of these artificial neurons, deep learning AI can perform extremely complex tasks like recognizing cats in videos or detecting tumors in biopsy images.

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📌Via: @cedeeplearning
social media: https://linktr.ee/cedeeplearning

link: https://theconversation.com/deep-learning-ai-discovers-surprising-new-antibiotics-132059

#deeplearning
#machinelearning
#neuralnetworks

🔹What are the limits of deep learning?

This example of what deep-learning researchers call an “adversarial attack,” discovered by the Google Brain team in Mountain View, CA (1), highlights just how far AI still has to go before it remotely approaches human capabilities. “I initially thought that adversarial examples were just an annoyance,” says Geoffrey Hinton, a computer scientist at the University of Toronto and one of the pioneers of deep learning.

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📌Via: @cedeeplearning

https://www.pnas.org/content/116/4/1074

#deeplearning
#machinelearning
#neuralnetworks
#datascience

🔹A new model of vision

Summary: A new computer model captures the human visual system’s ability to quickly generate a detailed scene denoscription from an image.

📗Source: MIT
When we open our eyes, we immediately see our surroundings in great detail. How the brain is able to form these richly detailed representations of the world so quickly is one of the biggest unsolved puzzles in the study of vision.

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📌Via: @cedeeplearning
📌social media: https://linktr.ee/cedeeplearning

link: https://neurosciencenews.com/computer-vision-15862/

#computervision
#deeplearning
#machinelearning
#neuralnetworks

🔹StyleGAN2

This article explores changes made in StyleGAN2 such as weight demodulation, path length regularization and removing progressive growing!

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📌Via: @cedeepleraning

https://towardsdatascience.com/stylegan2-ace6d3da405d

#GANs
#deeplearning
#cnn
#neuralnetworks
#machinelearning

Deepmind’s paper on solving mathematical equations

https://www.youtube.com/watch?v=f9z1I_81_Q4

📌 Via: @cedeeplearning
Other social media: https://linktr.ee/cedeeplearning

👇🏻👇🏻Using Deep Convolutional Neural Networks for Neonatal Brain Image Segmentation

📌Via: @cedeeplearning
📌Social media: https://linktr.ee/cedeeplearning

#cnn
#deeplearning
#neuralnetworks

🔹Using Deep Convolutional Neural Networks for Neonatal Brain Image Segmentation

Authors:
Yang Ding, Rolando Acosta

Deep learning neural networks are especially potent at dealing with structured data, such as images and volumes. Both modified LiviaNET and HyperDense-Net performed well at a prior competition segmenting 6-month-old infant magnetic resonance images, but neonatal cerebral tissue type identification is challenging given its uniquely inverted tissue contrasts. The current study aims to evaluate the two architectures to segment neonatal brain tissue types at term equivalent age.
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📌Via: @cedeeplearning
📌Social media: https://linktr.ee/cedeeplearning

link: http://www.thetalkingmachines.com/article/using-deep-convolutional-neural-networks-neonatal-brain-image-segmentation

#deeplearning
#neuralnetworks
#machinelearning
#cnn

🔹Exploring Nature-Inspired Robot Agility

Posted by Xue Bin (Jason) Peng, Student Researcher and Sehoon Ha, Research Scientist, Robotics at Google
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📌Via: @cedeeplearning

https://youtu.be/lKYh6uuCwRY

#machinelearning
#deeplearning
#neuralnetworks
#robotics
#AI

🔹How to Build Your Own Deep Learning Box

Want to build an affordable deep learning box and get all the required software installed? Read on for a proper overview.

Credit: By Hui Han Chin, DSO National Laboratories, Singapore.
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📌Via: @cedeeplearning

https://www.kdnuggets.com/2016/06/build-deep-learning-box.html

🎧 Nanotronics Brings Deep Learning to Precision Manufacturing - Ep. 109
(Podcast)

Matthew Putman, Ep.109’s guest on the AI Podcast, knows that the devil is in the details. That’s why he’s the co-founder and CEO of Nanotronics, a Brooklyn-based company providing precision manufacturing enhanced by AI, automation and 3D imaging.
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📌Via: @cedeeplearning

https://soundcloud.com/theaipodcast/ai-nanotronics-matthew-putman-3

🔻More Performance Evaluation Metrics for Classification Problems You Should Know

When building and optimizing your classification model, measuring how accurately it predicts your expected outcome is crucial. However, this metric alone is never the entire story, as it can still offer misleading results. That's where these additional performance evaluations come into play to help tease out more meaning from your model.

Credit: By Clare Liu
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📌Via: @cedeeplearning

https://www.kdnuggets.com/2020/04/performance-evaluation-metrics-classification.html

#machinelearning
#classification
#recall
#precision

Perform cross-modal translation from "in-the-wild'' monologue speech of a single speaker to their hand and arm motion.
The project website with video, code and data can be found at http://people.eecs.berkeley.edu/~shiry/speech2gesture.

* CVPR 2019

✅Via: @cedeeplearning
✅ Other social media handles: https://linktr.ee/cedeeplearning

Pixel Recurrent Neural Network

Pixel RNN sequentially predicts the pixels in an image along the two spatial dimensions. The method models the discrete probability of the raw pixel values and encodes the complete set of dependencies in the image.
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Paper: https://arxiv.org/abs/1601.06759
Via: @CEdeeplearning 📌
Other social media: https://linktr.ee/cedeeplearning
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#pixelrnn #generativemodel #computervision #rnn #cnn #neuralnetworks #deeplearning #machinelearning

“Facts are stubborn things, but statistics are pliable.”
― Mark Twain

📌Via: @cedeeplearning