Self introduction
- To give a brief introduction,Wine Rack is nearly 48 years old, has more than 20 years of IT work experience, and currently works in enterprise architecture for a Fortune 500 company. Because of work needs and because of my broad interests, I have established three blogs for my own learning, namely [Global IT Outlook], [Global IT Outlook] a>], there are more Content sharing, thank you for collecting it. Developer Chat] and [Architect Pub
- Enterprise architects need a broad range of knowledge to understand an enterprise's overall business, applications, technology, data, governance and compliance. In the previous four years, he was mainly responsible for the overall technical planning, standard establishment and project management of the enterprise. In the past year, I have been mainly responsible for data, involving data platform, data strategy, data analysis, data modeling, data governance, as well as data sovereignty, privacy protection and data economy. Because of the need, such as incorporating data resources into financial statements, and how to value and monetize data requires financial and financial knowledge, I have been studying finance, finance and law recently. I plan to prepare for the CPA first and then the CFA. If possible, I also want to study law and prepare for the bar exam.
- Students and friends who love learning are welcome to pay attention and everyone is welcome to communicate. WeChat account [ca_cea]
Innovations in Google's popular open source TensorFlow machine learning platform include automatic differentiation (Autograd) and the XLA (Accelerated Linear Algebra) optimizing compiler for deep learning. JAX, also from Google, is another project that brings these two technologies together, offering considerable benefits in terms of speed and performance. When running on a GPU or TPU, JAX can replace other programs that call NumPy, but its programs run faster. (The Autograd engine can automatically differentiate between native Python and NumPy code.) Additionally, using JAX for neural networks can make adding new features easier than extending larger frameworks like TensorFlow.
——Martin Heller
欢welding蔶藏 【Global IT Observation】、【Building Company Liquor Store】和【开发者开聊】.