🔻Top 10 Statistics Mistakes Made by Data Scientists

🔹by Norman Niemer

The following are some of the most common statistics mistakes made by data scientists. Check this list often to make sure you are not making any of these while applying statistics to data science.

1. Not fully understanding the objective function

2. Not having a hypothesis on why something should work

3. Not looking at the data before interpreting results

4. Not having a naive baseline model

5. Incorrect out-sample testing

6. Incorrect out-sample testing: applying preprocessing to full dataset

7. Incorrect out-sample testing: cross-sectional data & panel data

8. Not considering which data is available at point of decision

9. Subtle Overtraining

10. "need more data" fallacy
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📌Via: @cedeeplearning
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link: https://www.kdnuggets.com/2019/06/statistics-mistakes-data-scientists.html

#datascience
#machinelearning
#statistics
#github

Gift will allow MIT researchers to use artificial intelligence in a biomedical device

🔹by Maria Iacobo

Researchers in the MIT Department of Civil and Environmental Engineering (CEE) have received a gift to advance their work on a device designed to position living cells for growing human organs using acoustic waves. The Acoustofluidic Device Design with Deep Learning is being supported by Natick, Massachusetts-based MathWorks, a leading developer of mathematical computing software.
“One of the fundamental problems in growing cells is how to move and position them without damage,” says John R. Williams, a professor in CEE. “The devices we’ve designed are like acoustic tweezers.”
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📌Via: @cedeeplearning

http://news.mit.edu/2020/gift-to-mit-cee-artificial-intelligence-biomedical-device-0129

#deeplearning
#MIT #math
#machinelearning
#AI #datascience
#biomedical

Hi guys 👋🏿

From today we’ll be uploading “Introduction to Deep Learning” course by prof. Andrew Ng (Stanford lecturer and cofounder of coursera, deeplearning ai etc.)

🔹Make sure to send this awesome course to your friends.

If you have any suggestion or need a different course, don't hesitate to tell me: @pudax
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📌 @cedeeplearning
📌 Other social media: https://linktr.ee/cedeeplearning

⚪️ Introduction to Deep Learning by Andrew Ng

Source: Coursera

Neural Networks and Deep Learning (Course 1 of the Deep Learning Specialization)

🔖 Welcome (Deep Learning Specialization)
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📌Other social media: https://linktr.ee/cedeeplearning

#DeepLearning #NeuralNeworks
#machinelearning #AI #coursera
#free #python

🔻HOW TO SOLVE 90% OF NLP PROBLEMS: A STEP-BY-STEP GUIDE

🔹by Emmanuel Ameisen

Whether you are an established company or working to launch a new service, you can always leverage text data to validate, improve, and expand the functionalities of your product. The science of extracting meaning and learning from text data is an active topic of research called Natural Language Processing (#NLP).
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📌Via: @cedeeplearning

https://www.topbots.com/solve-ai-nlp-problems-guide/

#deeplearning
#neuralnetworks
#machinelearning
#text_data
#datascience

8 Ways Artificial Intelligence Takes Publishing to the Next Level | Hacker Noon

https://hackernoon.com/8-ways-artificial-intelligence-takes-publishing-to-the-next-level-rvnk3z3m

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

https://www.slashgear.com/breakthrough-electronic-cells-could-learn-like-a-human-brain-20617405/

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

🔹Google leverages computer vison to enhance the performance of robot manipulation

by Priya Dialani

The possibility that robots can figure out how to directly see the affordances of actions on objects (i.e., what the robot can or can’t do with an item) is called affordance-based manipulation, explored in research on learning complex vision-based manipulation skills including grasping, pushing, and tossing. In these #frameworks, affordances are represented as thick pixel-wise action-value maps that gauge how great it is for the #robot to execute one of a few predefined movements in every area.
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📌Via: @cedeeplearning

https://www.analyticsinsight.net/google-leverages-computer-vision-enhance-performance-robot-manipulation/

#computervision
#deeplearning
#neuralnetworks
#machinelearning

🔹Facial recognition in retail banking and IP surveillance
by Priya Dialani

In the last decade, we have seen an increase in the utilization of innovation in numerous business segments to improve and better connect with customers. This is particularly valid in the banking and finance division. Since the beginning of the #digital_revolution facial recognition has been picking up prominence over touch and type based interactions because of the convenience it offers without settling on the security of transactions. #Facial_recognition is one of the various ways banks can diminish friction in customers’ experience and increase productivity and availability.
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📌Via: @cedeeplearning
📌Other social media: https://linktr.ee/cedeeplearning

link: https://www.analyticsinsight.net/facial-recognition-in-retail-banking-and-ip-surveillance/

#imagerecognition
#facerecognition
#deeplearning
#AI #math #datascience

🔹Data Engineer VS Data Science

🔻The reign of data is upon us
this quote is something management consultants preach to their corporate customers. many looking to exploit their data. But a good first step to do this would be up front investment is data engineering.

🔻Who are Data Engineers?
Data engineers typically are responsible for #processing raw data and extracting that from source systems. They also build the #ingestion_layer, and the #infrastructure to process and enrich the data.

🔻Data Engineers and the business
They should have the technical chops but also be able to work directly on product teams, or Scrums alongside of subject matter experts and data scientists.
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📌Via: @cedeeplearning
📌Other social media: https://linktr.ee/cedeeplearning

link: https://analyticsnomad.com/data-engineering-vs-data-science/

#datascience
#machinelearning
#AI #dataengineer
#datascienctist

🔻Skills Needed to Become a Data Scientist (Learn, Grasp, Implement)

By DATAFLAIR TEAM

A data scientist is better statistician than any software engineer and better engineer as compared to any statistician. A data scientist is termed to be the “sexiest job of the 21st century.

🔻Do not miss out this article !
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📌Via: @cedeeplearning
📌Other social media: https://linktr.ee/cedeeplearning

link: https://data-flair.training/blogs/skills-needed-to-become-a-data-scientist/

#datascience
#datascientist
#skill #python #math
#machinelearning

⚪️ Introduction to Neural Networks by Andrew Ng

🔹Source: Coursera

Neural Networks and Deep Learning (Course 1 of the Deep Learning Specialization)

🔖 Lecture 0 About This Course
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#DeepLearning #NeuralNeworks
#machinelearning #AI #coursera
#free #python

🔻Is Deep Learning Overhyped?

With all of the success that deep learning is experiencing, the detractors and cheerleaders can be seen coming out of the woodwork. What is the real validity of deep learning, and is it simply hype?
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📌via: @cedeeplearning

https://www.kdnuggets.com/2016/01/deep-learning-overhyped.html

#deeplearning
#machinelearning
#hype #neuralnetworks
#Yoshua_Bengio

🔻Why Deep Learning is Radically Different From Machine Learning

🖊By Carlos Perez

There is a lot of confusion these days about Artificial Intelligence (AI), Machine Learning (ML) and Deep Learning (DL), yet the distinction is very clear to practitioners in these fields. Are you able to articulate the difference?
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📌Via: @cedeeplearning
📌Other social media: https://linktr.ee/cedeeplearning

link: https://www.kdnuggets.com/2016/12/deep-learning-radically-different-machine-learning.html

#deeplearning #machinelearning
#neuralnetworks #AI #ANN

🔹How Deep Learning is Accelerating Drug Discovery in Pharmaceuticals

🖊by Kevin Vu

The goal of this essay is to discuss meaningful machine learning progress in the real-world application of drug discovery. There’s even a solid chance of the deep learning approach to drug discovery changing lives for the better doing meaningful good in the world.
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📌Via: @cedeeplearning

https://www.kdnuggets.com/2020/04/deep-learning-accelerating-drug-discovery-pharmaceuticals.html

#deeplearning #neuralnetworks
#pharma #drug_development
#machinelearning #datascience

🔻Recent Advances for a Better Understanding of Deep Learning

🖊By Arthur Pesah.

A summary of the newest deep learning trends, including Non Convex Optimization, Over-parametrization and Generalization, Generative Models, Stochastic Gradient Descent (SGD) and more.

🔹Current areas of deep learning theory research, by dividing them into four branches:
1. Non Convex Optimization
2. Overparametrization and Generalization
3. Role of Depth
4. Generative Models
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📌Via: @cedeeplearning
📌Other social media: https://linktr.ee/cedeeplearning

link: https://www.kdnuggets.com/2018/10/recent-advances-deep-learning.html

#deeplearning #flatminima
#linearnetworks #optimization
#SGD #neuralnetworks
#machinelearning

🔻THE RISE OF COMPUTER VISION TECHNOLOGY

🖊by Preetipadma

A lot of factors have contributed to the revolutionizing success of AI. Computer Vision is one of those driving elements. It is a sequential integration of three distinct processes, i.e. acquisition of images or visual stimuli from the real world in the form of binary data, image processing in form of edge detection, segmentation matching and lastly analysis and interpretation. From augmented reality games to self-driving cars to Apple’s Facial Unlock feature, it has deeply impacted our life. And this influence is not free of consequences. However, on the flip side, it has been welcomed with generally encourage reviews.
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📌Via: @cedeeplearning

link: https://www.analyticsinsight.net/the-rise-of-computer-vision-technology/

#computervision #deeplearning
#neuralnetworks #imagedetection
#selfdrivingcars #machinelearning

🔻TECH ONE, ESCAPE ZERO: BODYCAMS EVOLVE WITH FACIAL RECOGNITION

👆🏻👆🏻👆🏻
🔻Tech one, escape zero: Bodycams evolve with facial recognition

🔹Facial recognition (FR) is enjoying a positive reception and widespread application these days. Enterprise, law enforcement and consumers are adopting FR to facilitate everything from administrative tasks, arresting suspects and unlocking cellphones. Although statistics that show law enforcement benefiting from employing facial recognition are still fresh, and typically center on petty criminals to date, many airports all over the world (but notably in the US) are also employing the technology for security and ease of boarding purposes.

🔹Sold to customers on the back of improved boarding speeds, airports are ideal venues to witness the facial recognition-enhanced consumer experience, while merging it with security concerns.

🔹American police officers have begun employing live facial recognition in their bodycams, a move authorities insist will aid police in their tasks and eliminate human error.
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📌Via: @cedeeplearning
📌Other social media: https://linktr.ee/cedeeplearning

link: https://www.analyticsinsight.net/tech-one-escape-zero-bodycams-evolve-facial-recognition/

#facerecognition #facial_recognition
#imagerecognition #imagedetection
#deeplearning #neuralnetworks

#Graph_Mining

🔴A SURVEY OF GRAPH MINING TECHNIQUES
FOR BIOLOGICAL DATASETS

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@cedeeplearning