Cutting Edge Deep Learning
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πŸ“• Deep learning
πŸ“— Reinforcement learning
πŸ“˜ Machine learning
πŸ“™ Papers - tools - tutorials

πŸ”— Other Social Media Handles:
https://linktr.ee/cedeeplearning
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πŸ”ΉDeep Learning #Cheatsheet

Activation function: #Activation functions are used at the end of a hidden unit to introduce #non-linear #complexities to the model. Here are the most common ones

from: stanford.edu
via: @cedeeplearning
πŸ”ΉWhat is Data Mining?
#Data_mining is a process of extracting the hidden #predictive information from the extensive database. Data mining is used by the organization to turn #raw_data into useful information.

link: https://statanalytica.com/data-mining-assignment-help

via: @cedeeplearning
πŸ”»How Does a Data Management Platform Work?

More than half of marketing organizations have deployed a marketing data management platform, yet confusion remains about what these solutions do β€” and what they don’t.

πŸ“Œ Via: @cedeeplearning

link: https://www.gartner.com/en/marketing/insights/articles/how-does-a-data-management-platform-work

#data_management
#platform
#DMP
πŸ”Ή85 Incredible
Data Visualization Examples
Although all kinds of these plots can be made using python or BI Tools like Power BI as well.

πŸ“Œ Via: @cedeeplearning

link: https://piktochart.com/data-visualization-examples/

#visualisation
#matplotlib
#python
#powerbi
πŸ”ΉStatistics Vs. Machine Learning

As an organization’s information infrastructure matures, the most appropriate next step is to begin adding advanced analytics. We use the specific term advanced analytics with purpose in this context for two few reasons:

πŸ”»It assumes migration from historical analytics into current and future based analytics
πŸ”»It encompasses statistical analysis as well as machine learning

πŸ“Œ Via: @cedeeplearning

link: https://www.rocketsource.co/blog/machine-learning-models/

#statistics
#machinelearning
#modeling
πŸ”ΉSuccessfully Deploying Machine Learning Models
There are various opinions and assertions out there regarding the end-to-end process of building and deploying predictive models. We strongly assert that the deployment process is not a process at all β€” it’s a lifecycle. Why? It’s an infinite process of iterations and improvements. Model deployment is in no way synonymous with model completion.

πŸ“Œ Via: @cedeeplearning

link: https://www.rocketsource.co/blog/machine-learning-models/

#end_to_end
#deployment
#machine_learning
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πŸ”» Massively Scaling Reinforcement Learning with SEED RL

Reinforcement learning (RL) has seen impressive advances over the last few years as demonstrated by the recent success in solving games such as Go and Dota 2. Models, or agents, learn by exploring an environment, such as a game, while optimizing for specified goals. However, current RL techniques require increasingly large amounts of training to successfully learn even simple games, which makes iterating research and product ideas computationally expensive and time consuming.

πŸ“Œ Via: @cedeeplearning

link: https://ai.googleblog.com/

#reinforcement
#RL
#deep_learning
#architecture
#training
πŸ”» Open Images V6 β€” Now Featuring Localized Narratives

Open Images is the largest annotated image dataset in many regards, for use in training the latest deep #convolutional #neural_networks for #computer_vision tasks. With the introduction of version 5 last May, the Open Images dataset includes 9M images annotated with 36M image-level labels, 15.8M bounding boxes, 2.8M instance #segmentations, and 391k visual relationships. Along with the dataset itself, the associated Open Images Challenges have spurred the latest advances in #object_detection, instance segmentation, and visual relationship detection.

πŸ“Œ Via: @cedeeplearning

link: https://ai.googleblog.com/search?updated-max=2020-03-11T09:00:00-07:00&max-results=10

#image_detection
#machinelearning
#deeplearning
πŸ”ΉHow Conversational AI creates new business cases

The era of conversational artificial intelligence is rapidly changing the business of both traditional websites and mobile applications. What are, then, the benefits of β€œconversational AI” that new business systems can offer? Well, to begin with: it seems that voice and dialogue interfaces are finally ripe to compete against traditional ones.

πŸ“Œ Via: @cedeeplearning

link: https://chatbotsmagazine.com/how-conversational-ai-create-new-business-cases-aed0740903c0

#AI
#business_case
#chatbot
#machine_learning
πŸ”»Where chatbots are headed in 2020

Chatbots are on the verge of living up to their hype, with new research commissioned by Intercom indicating where they can have the most impact.

πŸ“Œ Via: @cedeeplearning

link: https://chatbotsmagazine.com/where-chatbots-are-headed-in-2020-4e4cbf281fc9

#chatbot
#demand
#business_case
#machinelearning
πŸ”»Notable Machine Learning Statistics in 2020. Market Share & Data Analysis


Many view machine learning as synonymous with artificial intelligence. In reality, machine learning is but a subset of AI, making the latter perform tasks faster and more intelligently by providing it with learning capabilities. These benefits make machine learning a key component of AI, a fact that will be affirmed by the latest machine learning statistics.

πŸ“Œ Via: @cedeeplearning

link: https://financesonline.com/machine-learning-statistics/

#statistics
#data_analysis
#market
#machinelearning
πŸ”»AI MAY KILL THESE 5 JOBS BY 2030, SAY EXPERTSπŸ”»

1. Bookkeeping Clerks
2. Location-Based Jobs
3. Market Research Analyst
4. Retail Workers
5. Software Developers

πŸ“Œ Via: @cedeeplearning

link: https://analyticsindiamag.com/ai-may-kill-these-5-jobs-by-2030-say-experts/

#AI
#job
#machinelearning
#datascience
πŸ”ΉGoogle AI statistics show that the company’s deep learning prediction algorithm correctly diagnoses suspected tumors 89% of the time by analyzing medical heatmaps.

For comparison’s sake, a team of expert pathologists gave a correct diagnosis only 73% of the time. AI machine learning VS human statistics consistently show that medical AI is getting better and better at recognizing diseases that human doctors can’t detect.

πŸ“Œ Via: @cedeeplearning

credit: google AI

#google_ai
#deeplearning
#healthcare
πŸ”»Using #WaveNet technology to reunite #speech-impaired users with their original voices

This post details a recent project we undertook with #Google and #ALS campaigner Tim Shaw, as part of Google’s Euphonia project. We demonstrate an early proof of concept of how #text-to-speech technologies can synthesize a high-quality, natural sounding voice using minimal recorded speech data.

πŸ“Œ Via: @cedeeplearning

link:https://deepmind.com/blog/article/Using-WaveNet-technology-to-reunite-speech-impaired-users-with-their-original-voices

#deepearning #deepmind
#machinelearning