🔖 The Best NLP with Deep Learning Course is Free
Stanford's Natural Language Processing with Deep Learning is one of the most respected courses on the topic that you will find anywhere, and the course materials are freely available online.
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📌Via: @cedeeplearning
https://www.kdnuggets.com/2020/05/best-nlp-deep-learning-course-free.html
#deeplearning #NLP
#neuralnetworks
#machinelearning
#free #AI #math
Stanford's Natural Language Processing with Deep Learning is one of the most respected courses on the topic that you will find anywhere, and the course materials are freely available online.
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📌Via: @cedeeplearning
https://www.kdnuggets.com/2020/05/best-nlp-deep-learning-course-free.html
#deeplearning #NLP
#neuralnetworks
#machinelearning
#free #AI #math
KDnuggets
The Best NLP with Deep Learning Course is Free - KDnuggets
Stanford's Natural Language Processing with Deep Learning is one of the most respected courses on the topic that you will find anywhere, and the course materials are freely available online.
🔹🔹 A Holistic Framework for Managing Data Analytics Projects
Agile project management for Data Science development continues to be an effective framework that enables flexibility and productivity in a field that can experience continuous changes in data and evolving stakeholder expectations. Learn more about the leading approaches for developing Data Science models, and apply them to your next project.
🔻The Data Science Delivery Process
Data science initiatives are project-oriented, so they have a defined start and end. The Cross-Industry Standard Process for Data Mining (CRISP-DM) is a high-level, extensible process that is an effective framework for data science projects.
Although the steps are shown in the general order in which they are executed, it is important to note that CRISP-DM, like the Agile software development process, is an iterative process framework. Each step can be revisited as many times as needed to refine problem understanding and results.
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📌Via: @cedeeplearning
https://www.kdnuggets.com/2020/05/framework-managing-data-analytics-projects.html
#Agile #CRISP_DM #Data_Analytics #Data_Management #Data_Mining #datascience #Decision_Management, #Development #Software Engineering
Agile project management for Data Science development continues to be an effective framework that enables flexibility and productivity in a field that can experience continuous changes in data and evolving stakeholder expectations. Learn more about the leading approaches for developing Data Science models, and apply them to your next project.
🔻The Data Science Delivery Process
Data science initiatives are project-oriented, so they have a defined start and end. The Cross-Industry Standard Process for Data Mining (CRISP-DM) is a high-level, extensible process that is an effective framework for data science projects.
Although the steps are shown in the general order in which they are executed, it is important to note that CRISP-DM, like the Agile software development process, is an iterative process framework. Each step can be revisited as many times as needed to refine problem understanding and results.
————————
📌Via: @cedeeplearning
https://www.kdnuggets.com/2020/05/framework-managing-data-analytics-projects.html
#Agile #CRISP_DM #Data_Analytics #Data_Management #Data_Mining #datascience #Decision_Management, #Development #Software Engineering
KDnuggets
A Holistic Framework for Managing Data Analytics Projects - KDnuggets
Agile project management for Data Science development continues to be an effective framework that enables flexibility and productivity in a field that can experience continuous changes in data and evolving stakeholder expectations. Learn more about the leading…
👆🏻👆🏻 A Holistic Framework for Managing Data Analytics Projects
🔻 The six CRISP-DM steps are:
1. Business Understanding
2. Data Understanding
3. Data Preparation
4. Modeling
5. Evaluation
6. Deployment
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📌Via: @cedeeplearning
📌Other social media: https://linktr.ee/cedeeplearning
link: https://www.kdnuggets.com/2020/05/framework-managing-data-analytics-projects.html
#data_management #datamining
#datascience #machinelearning
#preprocessing #agile #project
🔻 The six CRISP-DM steps are:
1. Business Understanding
2. Data Understanding
3. Data Preparation
4. Modeling
5. Evaluation
6. Deployment
—————————
📌Via: @cedeeplearning
📌Other social media: https://linktr.ee/cedeeplearning
link: https://www.kdnuggets.com/2020/05/framework-managing-data-analytics-projects.html
#data_management #datamining
#datascience #machinelearning
#preprocessing #agile #project
🔹🔹 Autonomous vehicle landscape 2020: The leaders of self-driving cars race
Self-Driving Car is yet to take a leap from sci-fi to real-world application. With rising debates and discussions at scale regarding the rollout of the autonomous vehicle, people are skeptical about its service towards them. However, far-far away from ordinary man’s thoughts, in the land of innovative technologies and amid top-notch leaders of the race of innovation, self-driving cars are no more a far-off star.
⚪️ Moreover, according to Bloomberg, here the top 5 leaders of autonomous vehicles landscape in 2020:
🔹 Waymo
Investment: US$3 billion
🔹 Cruise
Investment: US$9+ billion
🔹 Argo AI
Investment: US$2.6 billion (VW); US$1 billion (Ford)
🔹 Aurora
Investment: US$700+ million
🔹 Aptiv
Investment: Undisclosed
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📌Via: @cdedeeplearning
https://www.analyticsinsight.net/autonomous-vehicle-landscape-2020-leaders-self-driving-cars-race/
#deeplearning #neuralnetworks
#machinelearning
#self_driving_cars
#datascience
Self-Driving Car is yet to take a leap from sci-fi to real-world application. With rising debates and discussions at scale regarding the rollout of the autonomous vehicle, people are skeptical about its service towards them. However, far-far away from ordinary man’s thoughts, in the land of innovative technologies and amid top-notch leaders of the race of innovation, self-driving cars are no more a far-off star.
⚪️ Moreover, according to Bloomberg, here the top 5 leaders of autonomous vehicles landscape in 2020:
🔹 Waymo
Investment: US$3 billion
🔹 Cruise
Investment: US$9+ billion
🔹 Argo AI
Investment: US$2.6 billion (VW); US$1 billion (Ford)
🔹 Aurora
Investment: US$700+ million
🔹 Aptiv
Investment: Undisclosed
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📌Via: @cdedeeplearning
https://www.analyticsinsight.net/autonomous-vehicle-landscape-2020-leaders-self-driving-cars-race/
#deeplearning #neuralnetworks
#machinelearning
#self_driving_cars
#datascience
Analytics Insight
Autonomous Vehicle Landscape 2020: The Leaders of Self-Driving Cars Race
Autonomous Vehicle industry is thriving at a great pace. The leaders of Self-Driving Cars market like Waymo, Cruise, Aurora and others are leveraging AI technologies and making high scale investments to drive better prospects.
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⚪️ Basics of Neural Network Programming
✒️ by prof. Andrew Ng
🔹Source: Coursera
🔖 Lecture 9 Computation Graph
Neural Networks and Deep Learning
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📌Via: @cedeeplearning
📌Other social media: https://linktr.ee/cedeeplearning
#DeepLearning #NeuralNeworks
#machinelearning #AI #coursera
#free #python #supervised_learning
#classification #logistic_regression
#graph #computation_graph
✒️ by prof. Andrew Ng
🔹Source: Coursera
🔖 Lecture 9 Computation Graph
Neural Networks and Deep Learning
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📌Via: @cedeeplearning
📌Other social media: https://linktr.ee/cedeeplearning
#DeepLearning #NeuralNeworks
#machinelearning #AI #coursera
#free #python #supervised_learning
#classification #logistic_regression
#graph #computation_graph
🔻 Deep learning accurately stains digital biopsy slides
Pathologists who examined the computationally stained images could not tell them apart from traditionally stained slides.
🔹 This process of computational digital staining and de-staining preserves small amounts of tissue biopsied from cancer patients and allows researchers and clinicians to analyze slides for multiple kinds of diagnostic and prognostic tests, without needing to extract additional tissue sections.
A Good Read 👌
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📌Via: @cedeeplearning
http://news.mit.edu/2020/deep-learning-provides-accurate-staining-digital-biopsy-slides-0522
#deeplearning #machinelearning
#neuralnetworks
#MIT #math #AI
Pathologists who examined the computationally stained images could not tell them apart from traditionally stained slides.
🔹 This process of computational digital staining and de-staining preserves small amounts of tissue biopsied from cancer patients and allows researchers and clinicians to analyze slides for multiple kinds of diagnostic and prognostic tests, without needing to extract additional tissue sections.
A Good Read 👌
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📌Via: @cedeeplearning
http://news.mit.edu/2020/deep-learning-provides-accurate-staining-digital-biopsy-slides-0522
#deeplearning #machinelearning
#neuralnetworks
#MIT #math #AI
MIT News
Deep learning accurately stains digital biopsy slides
Digital scans of biopsy slides can be stained computationally, using deep learning algorithms trained on data from physically dyed slides, according to a research team led by MIT scientists at the Media Lab.
⚪️ Visualizing the world beyond the frame
🔹Researchers test how far artificial intelligence models can go in dreaming up varied poses and colors of objects and animals in photos.
🔹To give computer vision models a fuller, more imaginative view of the world, researchers have tried feeding them more varied images. Some have tried shooting objects from odd angles, and in unusual positions, to better convey their real-world complexity. Others have asked the models to generate pictures of their own, using a form of artificial intelligence called GANs, or generative adversarial networks. In both cases, the aim is to fill in the gaps of image datasets to better reflect the three-dimensional world and make face- and object-recognition models less biased.
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📌Via: @cedeeplearning
📌Other social media: https://linktr.ee/cedeeplearning
link: http://news.mit.edu/2020/visualizing-the-world-beyond-the-frame-0506
#deeplearning #GANs #math
#machinelearning #visualization
#AI #MIT #datascience
🔹Researchers test how far artificial intelligence models can go in dreaming up varied poses and colors of objects and animals in photos.
🔹To give computer vision models a fuller, more imaginative view of the world, researchers have tried feeding them more varied images. Some have tried shooting objects from odd angles, and in unusual positions, to better convey their real-world complexity. Others have asked the models to generate pictures of their own, using a form of artificial intelligence called GANs, or generative adversarial networks. In both cases, the aim is to fill in the gaps of image datasets to better reflect the three-dimensional world and make face- and object-recognition models less biased.
——————
📌Via: @cedeeplearning
📌Other social media: https://linktr.ee/cedeeplearning
link: http://news.mit.edu/2020/visualizing-the-world-beyond-the-frame-0506
#deeplearning #GANs #math
#machinelearning #visualization
#AI #MIT #datascience
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⚪️ Basics of Neural Network Programming
✒️ by prof. Andrew Ng
🔹Source: Coursera
🔖 Lecture 10 Derivatives With Computation Graphs
Neural Networks and Deep Learning
——————————
📌Via: @cedeeplearning
📌Other social media: https://linktr.ee/cedeeplearning
#DeepLearning #NeuralNeworks
#machinelearning #AI #coursera
#free #python #supervised_learning
#classification #logistic_regression
#graph #computation_graph
✒️ by prof. Andrew Ng
🔹Source: Coursera
🔖 Lecture 10 Derivatives With Computation Graphs
Neural Networks and Deep Learning
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📌Via: @cedeeplearning
📌Other social media: https://linktr.ee/cedeeplearning
#DeepLearning #NeuralNeworks
#machinelearning #AI #coursera
#free #python #supervised_learning
#classification #logistic_regression
#graph #computation_graph
⭕️ A foolproof way to shrink deep learning models
Researchers unveil a pruning algorithm to make artificial intelligence applications run faster.
🖋By Kim Martineau
As more artificial intelligence applications move to smartphones, deep learning models are getting smaller to allow apps to run faster and save battery power. Now, MIT researchers have a new and better way to compress models.
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📌Via: @cedeeplearning
http://news.mit.edu/2020/foolproof-way-shrink-deep-learning-models-0430
#deeplearning #AI #model
#MIT #machinelearning
#datascience #neuralnetworks
#algorithm #research
Researchers unveil a pruning algorithm to make artificial intelligence applications run faster.
🖋By Kim Martineau
As more artificial intelligence applications move to smartphones, deep learning models are getting smaller to allow apps to run faster and save battery power. Now, MIT researchers have a new and better way to compress models.
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📌Via: @cedeeplearning
http://news.mit.edu/2020/foolproof-way-shrink-deep-learning-models-0430
#deeplearning #AI #model
#MIT #machinelearning
#datascience #neuralnetworks
#algorithm #research
MIT News
A foolproof way to shrink deep learning models
MIT researchers have proposed a technique for shrinking deep learning models that they say is simpler and produces more accurate results than state-of-the-art methods. It works by retraining the smaller, pruned model at its faster, initial learning rate.
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⚪️ Basics of Neural Network Programming
✒️ by prof. Andrew Ng
🔹Source: Coursera
🔖 Lecture 11 Logistic Regression Gradient Descent
Neural Networks and Deep Learning
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📌Via: @cedeeplearning
📌Other social media: https://linktr.ee/cedeeplearning
#DeepLearning #NeuralNeworks
#machinelearning #AI #coursera
#free #python #supervised_learning
#classification #logistic_regression
#gradient #gradient_descent
✒️ by prof. Andrew Ng
🔹Source: Coursera
🔖 Lecture 11 Logistic Regression Gradient Descent
Neural Networks and Deep Learning
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📌Via: @cedeeplearning
📌Other social media: https://linktr.ee/cedeeplearning
#DeepLearning #NeuralNeworks
#machinelearning #AI #coursera
#free #python #supervised_learning
#classification #logistic_regression
#gradient #gradient_descent
🔋 Machine-learning tool could help develop tougher materials
Engineers develop a rapid screening system to test fracture resistance in billions of potential materials.
🖊 By David L. Chandler
For engineers developing new materials or protective coatings, there are billions of different possibilities to sort through. Lab tests or even detailed computer simulations to determine their exact properties, such as toughness, can take hours, days, or more for each variation. Now, a new artificial intelligence-based approach developed at MIT could reduce that to a matter of milliseconds, making it practical to screen vast arrays of candidate materials.
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📌Via: @cedeeplearning
http://news.mit.edu/2020/machine-learning-develop-materials-0520
#machinelearning #deeplearning
#neuralnetworks #material #AI
#datascience #MIT #engineering
Engineers develop a rapid screening system to test fracture resistance in billions of potential materials.
🖊 By David L. Chandler
For engineers developing new materials or protective coatings, there are billions of different possibilities to sort through. Lab tests or even detailed computer simulations to determine their exact properties, such as toughness, can take hours, days, or more for each variation. Now, a new artificial intelligence-based approach developed at MIT could reduce that to a matter of milliseconds, making it practical to screen vast arrays of candidate materials.
————————
📌Via: @cedeeplearning
http://news.mit.edu/2020/machine-learning-develop-materials-0520
#machinelearning #deeplearning
#neuralnetworks #material #AI
#datascience #MIT #engineering
MIT News
Machine-learning tool could help develop tougher materials
For engineers developing new materials or protective coatings, there are billions of different possibilities to sort through; lab tests or computer simulations can take hours, days, or more. A new MIT artificial-intelligence-based approach could dramatically…
❌ Deep learning is a blessing to police for crime investigations
Deep learning architectures these days are applied to computer vision, speech recognition, machine translation, bioinformatics, drug design, crime inspections and various other fields. Deep learning uses deep neural networks based on which actions are triggered and have produced results comparable to human experts. When compared to traditional machine learning algorithms which are linear, deep learning algorithms are hierarchical. These are based on increasing complexity and abstraction. Now, these are helpful in police investigations in the way these processes available information.
In the police investigations, deep learning helps through the video analysis. Videos gathered from multiple sources are feed into the deep learning systems. Through the software, we can identify and differentiate various targets appearing on the footage.
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📌 Via: @cedeeplearning
https://www.analyticsinsight.net/deep-learning-is-a-blessing-to-police-for-investigations/
#deeplearning #machinelearning
#neuralnetworks #videodetection
#analysis #AI #math #datascience
#artificial_intelligence
Deep learning architectures these days are applied to computer vision, speech recognition, machine translation, bioinformatics, drug design, crime inspections and various other fields. Deep learning uses deep neural networks based on which actions are triggered and have produced results comparable to human experts. When compared to traditional machine learning algorithms which are linear, deep learning algorithms are hierarchical. These are based on increasing complexity and abstraction. Now, these are helpful in police investigations in the way these processes available information.
In the police investigations, deep learning helps through the video analysis. Videos gathered from multiple sources are feed into the deep learning systems. Through the software, we can identify and differentiate various targets appearing on the footage.
————————
📌 Via: @cedeeplearning
https://www.analyticsinsight.net/deep-learning-is-a-blessing-to-police-for-investigations/
#deeplearning #machinelearning
#neuralnetworks #videodetection
#analysis #AI #math #datascience
#artificial_intelligence
www.analyticsinsight.net
Deep Learning Is a Blessing to Police for Crime Investigations |
Deep learning has penetrated deep into the system which can be more helpful in crime investigation and analysis for police. Deep learning differs from artificial intelligence and is a part of a broader family of machine learning.
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⚪️ Basics of Neural Network Programming
✒️ by prof. Andrew Ng
🔹Source: Coursera
🔖 Lecture 12 Gradient Descent on m Examples
Neural Networks and Deep Learning
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📌Via: @cedeeplearning
📌Other social media: https://linktr.ee/cedeeplearning
#DeepLearning #NeuralNeworks
#machinelearning #AI #coursera
#free #python #supervised_learning
#classification #logistic_regression
#gradient #gradient_descent
✒️ by prof. Andrew Ng
🔹Source: Coursera
🔖 Lecture 12 Gradient Descent on m Examples
Neural Networks and Deep Learning
——————————
📌Via: @cedeeplearning
📌Other social media: https://linktr.ee/cedeeplearning
#DeepLearning #NeuralNeworks
#machinelearning #AI #coursera
#free #python #supervised_learning
#classification #logistic_regression
#gradient #gradient_descent
🔹🔹 Deep Learning for Detecting Pneumonia from X-ray Images
🖊By Abhinav Sagar
🔻This article covers an end to end pipeline for pneumonia detection from X-ray images.
⚪️ Environment and tools
scikit-learn
keras
numpy
pandas
matplotlib
🔻🔻Do not miss out this article!!
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📌Via: @cedeeplearning
https://www.kdnuggets.com/2020/06/deep-learning-detecting-pneumonia-x-ray-images.html
#deeplearning #python
#machinelearning #numpy
#pandas #matplotlib
#keras #scikit_learn #healthcare #image_recognition
🖊By Abhinav Sagar
🔻This article covers an end to end pipeline for pneumonia detection from X-ray images.
⚪️ Environment and tools
scikit-learn
keras
numpy
pandas
matplotlib
🔻🔻Do not miss out this article!!
————————
📌Via: @cedeeplearning
https://www.kdnuggets.com/2020/06/deep-learning-detecting-pneumonia-x-ray-images.html
#deeplearning #python
#machinelearning #numpy
#pandas #matplotlib
#keras #scikit_learn #healthcare #image_recognition
KDnuggets
Deep Learning for Detecting Pneumonia from X-ray Images
This article covers an end to end pipeline for pneumonia detection from X-ray images.
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⚪️ Basics of Neural Network Programming
✒️ by prof. Andrew Ng
🔹Source: Coursera
🔖 Lecture 13 Vectorization
Neural Networks and Deep Learning
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📌Via: @cedeeplearning
📌Other social media: https://linktr.ee/cedeeplearning
#DeepLearning #NeuralNeworks
#machinelearning #AI #coursera
#free #python #supervised_learning
#classification #vectorization
✒️ by prof. Andrew Ng
🔹Source: Coursera
🔖 Lecture 13 Vectorization
Neural Networks and Deep Learning
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📌Via: @cedeeplearning
📌Other social media: https://linktr.ee/cedeeplearning
#DeepLearning #NeuralNeworks
#machinelearning #AI #coursera
#free #python #supervised_learning
#classification #vectorization
⚪️ Metis Webinar: Deep Learning Approaches to Forecasting
🔹Metis Corporate Training is offering Deep Learning Approaches to Forecasting and Planning, a free webinar focusing on the intuition behind various deep learning approaches, and exploring how business leaders, data science managers, and decision makers can tackle highly complex models by asking the right questions, and evaluating the models with familiar tools.
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📌Via: @cedeeplearning
📌Other social media: https://linktr.ee/cedeeplearning
link: https://www.kdnuggets.com/2020/06/metis-webinar-deep-learning-approaches-forecasting.html
#deeplearning #forecasting #metis #webinar #machinelearning #neuralnetworks #free #datascience
🔹Metis Corporate Training is offering Deep Learning Approaches to Forecasting and Planning, a free webinar focusing on the intuition behind various deep learning approaches, and exploring how business leaders, data science managers, and decision makers can tackle highly complex models by asking the right questions, and evaluating the models with familiar tools.
————————
📌Via: @cedeeplearning
📌Other social media: https://linktr.ee/cedeeplearning
link: https://www.kdnuggets.com/2020/06/metis-webinar-deep-learning-approaches-forecasting.html
#deeplearning #forecasting #metis #webinar #machinelearning #neuralnetworks #free #datascience
🔹 How to Think Like a Data Scientist
🖊By Jo Stichbury
🔻So what does it take to become a data scientist? For some pointers on the skills for success, I interviewed Ben Chu, who is a Senior Data Scientist at Refinitiv Labs.
🔻Be curious
🔻Be scientific
🔻Be creative
🔻Learn how to code
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📌Via: @cedeeplearning
https://www.kdnuggets.com/2020/05/think-like-data-scientist-data-analyst.html
#datascience #machinelearning
#tutorial #roadmap
#python #math #statistics #neuralnetworks
🖊By Jo Stichbury
🔻So what does it take to become a data scientist? For some pointers on the skills for success, I interviewed Ben Chu, who is a Senior Data Scientist at Refinitiv Labs.
🔻Be curious
🔻Be scientific
🔻Be creative
🔻Learn how to code
——————
📌Via: @cedeeplearning
https://www.kdnuggets.com/2020/05/think-like-data-scientist-data-analyst.html
#datascience #machinelearning
#tutorial #roadmap
#python #math #statistics #neuralnetworks
KDnuggets
How to Think Like a Data Scientist - KDnuggets
So what does it take to become a data scientist? For some pointers on the skills for success, I interviewed Ben Chu, who is a Senior Data Scientist at Refinitiv Labs.
🔹 Study by - LinkedIn Learning.
some important skills needed by companies for 2020
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📌Via: @cedeeplearning
📌Other social media:https://linktr.ee/cedeeplearning
#skill #python #machinelearning #computerscience #datascience
#tutorial #softskills #hardskills
some important skills needed by companies for 2020
———————
📌Via: @cedeeplearning
📌Other social media:https://linktr.ee/cedeeplearning
#skill #python #machinelearning #computerscience #datascience
#tutorial #softskills #hardskills
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⚪️ Basics of Neural Network Programming
✒️ by prof. Andrew Ng
🔹Source: Coursera
🔖 Lecture 14 More Vectorization Examples
Neural Networks and Deep Learning
——————————
📌Via: @cedeeplearning
📌Other social media: https://linktr.ee/cedeeplearning
#DeepLearning #NeuralNeworks
#machinelearning #AI #coursera
#free #python #supervised_learning
#classification #vectorization
✒️ by prof. Andrew Ng
🔹Source: Coursera
🔖 Lecture 14 More Vectorization Examples
Neural Networks and Deep Learning
——————————
📌Via: @cedeeplearning
📌Other social media: https://linktr.ee/cedeeplearning
#DeepLearning #NeuralNeworks
#machinelearning #AI #coursera
#free #python #supervised_learning
#classification #vectorization