Businessintelligence, machinelearning, deeplearning, tfhub & much more…
AI News Sunday, July 15
- What do machine learning practitioners actually do? · fast.ai
- Google Colaboratory
- Artificial Intelligence : The Risks and Benefits
- What’s the Difference Between AI, Machine Learning, and Deep Learning?
- Google Colaboratory
- Sponsorship Opportunities For @CloudEXPO New York Open
BigData, AI, DevOps, IoT
- AI adoption at the atomic level of jobs and work
MachineLearning, ArtificialInteligence, AI
- Artificial Intelligence: Startup Hackrod – Digitalization & Software – Pictures of the Future – Innovation – Home – Siemens Global Website
3Dprinter, AI, DigitalTwin, Software, Automation, UnlockThePotential, FOS
- China International Robot Show: What’s the smart thinking on AI? – CGTN
- Comprehensive Repository of Data Science and ML Resources
DataScience, MachineLearning, NeuralNetworks, abdsc, BigData, AI, DeepLearning, DataScientists
- It will address what it is that machine learning practitioners do, with Part 2 explaining AutoML and neural architecture search (which several high profile figures have suggested will be key to decreasing the need for data scientists) and Part 3 will cover Googles heavily hyped AutoML product in particular.
- The authors identify a number of system-level interactions, risks, and anti-patterns, including: – – The authors write, A remarkable portion of real-world machine learning work is devoted to tackling issues of this form… Its worth noting that glue code and pipeline jungles are symptomatic of integration issues that may have…
- (emphasis mine) – – In a previous post, I identified some failure modes in which machine learning projects are not effective in the workplace: – – I framed these as organizational failures in my original post, but they can also be described as various participants being overly focused on just…
- Here are some of the things that machine learning practitioners may need to do during the process: – – Certainly, not every machine learning practitioner needs to do all of the above steps, but components of this process will be a part of many machine learning applications.
- For myself and many others I know, I would highlight two of the most time-consuming and frustrating aspects of machine learning (in particular, deep learning) as: – – Dealing with data formatting, inconsistencies, and errors is often a messy and tedious process.
@jonojace: What do machine learning practitioners actually do? https://t.co/euhwaGUZET
@random_forests: Happy Saturday! Here’s an updated tutorial to train a linear classifier using an Estimator and feature columns, with eager execution enabled to debug the input functions: https://t.co/JwHTwEg6Ze
- Looking for Professional Strategy Services?
- Digital Marketing Manager + Competitive Analysis Strategy
@rubengarciaes: Artificial Intelligence : The Risks and Benefits https://t.co/GzMdbr8gAs #businessintelligence
- Machine learning is a subset of AI, and it consists of the techniques that enable computers to figure things out from the data and deliver AI applications.
- Deep learning, meanwhile, is a subset of machine learning that enables computers to solve more complex problems.
- Lets look at a couple of problems to see how deep learning is different from simpler neural networks or other forms of machine learning.
- There are many techniques for AI, but one subset of that bigger list is machine learning let the algorithms learn from the data.
- Finally, deep learning is a subset of machine learning, using many-layered neural networks to solve the hardest (for computers) problems.
@java: What’s the Difference Between AI, #MachineLearning, and #DeepLearning https://t.co/zqM9tACvxN https://t.co/BpnKGg8ZOo
@TensorFlow: This paper includes 15 TensorFlow Hub modules to generate images using GANs! Check out the colab notebook to try it out → https://t.co/h69ra0odpC #TFHub https://t.co/3ARRRLCfaf
@TheIoT: Sponsorship Opportunities For @CloudEXPO New York Open | #BigData #AI #DevOps… https://t.co/lWKBPxTzKN #IoT
@TheAIConf: [O’Reilly Radar podcast] @dbeyer123 discusses #MachineLearning and #ArtificialInteligence, the complexities of #AI adoption, and what’s missing from the AI conversation https://t.co/idfSlX72VL
Artificial Intelligence: Startup Hackrod – Digitalization & Software – Pictures of the Future – Innovation – Home – Siemens Global Website
@Siemens: Welcome to the world’s probably biggest #3Dprinter. Our colleagues from @Hackrod_Inc are using it to print sportscars – thanks to #AI, our #DigitalTwin #Software and our #Automation solutions. Learn more: https://t.co/pV9ISfDkXX #UnlockThePotential #FOS https://t.co/KPMViw9Xto
@CGTNOfficial: #ICYMI China International Robot Show: What’s the smart thinking on #AI? https://t.co/V3B0qsGTS6 https://t.co/t2MAtsdmq8
@KirkDBorne: Comprehensive Repository of #DataScience and #MachineLearning Resources, including “22 Great Articles About #NeuralNetworks” 👉 https://t.co/qz1nRPwWRL #abdsc #BigData #AI #DeepLearning #DataScientists https://t.co/KrTL5m4UMP