A key challenge in #ReinforcementLearning is learning policies from scratch in environments with complex tasks. Read how a meta-algorithm, Jump Start Reinforcement Learning, uses prior policies to create a learning curriculum that improves performance → https://t.co/CkFLof4fNp
Aún recuerdo cuando con una #kinect y #opencv nos peleabamos para tener un modelo 3D decente para los #robóts. Y esta gente lo hace así de fácil, chás: "3D Scene Understanding with #TensorFlow 3D" #ai https://t.co/gKtWA15t5C
In functional API allows you to create models that have a lot more flexibility as you can easily define models where layers connect to more than just the previous and next layers
My year on #Github2020 🐙 aadhil96
📬 Commits/Issues/PRs: 52
🏝️ Repos contributed to: 7
⭐ New stars: 2
🔥 Hottest: aadhil96/covid19_analysis_and_prediction (+2)
Share yours: https://t.co/SGJU5ebxzg | Built by @jrieke w/ @streamlit
Here my article about time series forecasting using Facebook's Prophet Model.Prophet is a procedure for forecasting time series data based on an additive model where non-linear trends.
https://t.co/REIqxwFYrV
Lets Talk about TensorFlow 2.0 on 28th December. Host by FOSS Community RUSL
Join using this link : https://t.co/2RduH0XAlG
#artificialintelligence#tensorflow