A summary of recent happenings in the field of Artificial Intelligence (AI) for week 34 of 2020. For more regular updates and related discussions, join us on the Artificial Intelligence Community. As always thanks for your support for sharing it with your friends and colleagues on social media.
Industry updates for week 34 of 2020
This section is for recent industry updates related to Artificial Intelligence.
- Crash Detection: AI-based Canadian company, MicroTraffic is using video analytics to predict accidents occurring at intersections and their prototype is trial-tested in more than 40 Canadian and US cities.
- Facebook’s SoundSpaces: Facebook’s AI team has crossed a milestone through SoundSpaces, audio-visual navigation in the 3D environment. It employs reinforcement learning for training and to read more visit this link.
- GPT3 has scope for improvement: This post by Gary Marcus and Ernest Davis brings to light the not so impressive outcomes of GPT3 and mentions the poor grasp of reality.
Articles for week 34 of 2020
This section is for recent Blog Post/Tutorials related to Artificial Intelligence.
- Outlier Detection Algorithms: Machine Learning Mastery’s updated thorough article based on four methods to detect outliers in the datasets is a must read.
- Selecting the right Features: Another nice read on getting a score for features to select the right one for our application is explained here.
- All you need to know about Deep Learning: Andreas Maier teaches Deep Learning at FAU, Germany, has put up his lecture videos and certain notes for free that can be referred here.
- Improving Hyperparameters for Scikit Learn: Optuna Framework can be used to obtain hyper-parameters for any Scikit Learn model. The blog explains Random Forest and Logistic Regression implementations and rest can be implemented similarly. Read more here.
- Learning python for free: This is an online version of Slither into Python and the book can also be purchased here.
- Best ML books: Here’s a blog post that combines a list from 30 other blog posts to get us the best ML books of the millennium or at least up to 2020.
- Data Experimentation during Pandemic: Rapido Labs has jotted down various approaches that need to be kept in mind as this pandemic is accompanied by many challenges. The entire article can be read here.
- Transforming statues using AI: Daniel Voshart, a creative designer whose pet project during t his pandemic was to bring old statues to life through his new hobby – colorizing old statues
This section is for recent Tools/Applications related to Artificial Intelligence.
- Spark-NLP: John Snow Labs Spark NLP is a NLP library built on top of Apache Spark ML. Its significant features include NLP annotations for ML pipelines and is easily scalable in any distributed environment. The GitHub repository is available here.
- minGPT: Andrej Karpathy’s minGPT is PyTorch re-implementation GPT training. The min GPT is supposed to clean, interpretable, and can be found here.
- SciML new release: SciML, an open-source firm is up with its new release that quite a handful of promising features including using neural networks to solve differential equations, solving higher-dimensional nonlinear Black-Scholes PDEs via forward-backwards SDEs, etc. Their full release can be found here.
- DeepMind’s new release: DeepMind has released its Jax libraries, Optax, and Chex for optimization and better code readability.
- Guide to Sequential Model: Updated Keras repository with more examples can be accessed here.
This section is for recent Lectures/Conferences/Webinars related to Artificial Intelligence.
- Alexa and Friends: On August 27th, 2020, Daniel Marco, Director at Amazon Alexa will be guest appearing on a show hosted by Jeff Blankenburg to speak on advancements in NLP in Alexa. To join the session follow the link here.
- Learn Jupyter with Bloomberg: Choosing a Data Source: A webinar on 25th August 2020, To register click here.
This section is for recent research published related to Artificial Intelligence.
This section is for other various recent Hardware/Books etc. related to Artificial Intelligence.
- Translate Survey: the University of Berkeley along with Google are surveying to improvise their translate and data collection purposes. The survey can be taken here.
- Graph Representation Learning: A pre-publication copy written by William Hamilton is available here.
That’s all for the week 34 of 2020. In case you think we have missed out something and that is significant to add, please free to reach out and submit to us via our Contact form or via Social media channels: Twitter and Facebook.