Machine Learning

In the field of machine learning, the amount of data is undoubtedly the big concern. However, for machine learning application algorithms and detection modes, they need to receive data in a meaningful way. Therefore, machine learning can benefit from the data system built by the Lambda architecture and the various types of data processed. According to this, machine learning algorithms can ask various questions and gradually perform pattern recognition on the data input into the system.

IOT

If machine learning uses the output of the Lambda architecture, then the Internet of Things uses the input of the data system more. Imagine…

Natural language processing (NLP) has become one of the most important fields in data science. Natural language processing (NLP) is the general term for natural language understanding (NLU), natural language generation (NLG), and natural language interaction (NLI).

Nowadays, natural language technology is increasingly used in enterprises. Many companies have developed numerous text analysis, speech recognition, chatbots, and all imaginable language processing use cases.

With the continuous development and innovation of technology companies such as Google and Microsoft, natural language processing (NLP) has achieved leaps and bounds in accuracy, speed, and methods, which can help computer scientists solve more complex problems…

What is DCA

Dollar-cost averaging (DCA) refers to the purchase of a smaller number of assets within a specified time interval no matter how the price changes. Of course, most people will at least try to grasp the time to buy when the short-term market is down, but the problem is that this buying strategy can reduce the risk of investing too much money at once.

To use DCA, you first need to decide how much money you are willing to invest, and then you need to buy a smaller equivalent amount of money within a specific period of time instead of investing…

Basic Idea

For the design of a new startup application, the most important thing is to clearly sort out the business model, analyze the business model, and make the system architecture based on the business characteristics to avoid many detours.

First, you have to determine the core functions required by each module of your business operations, the business modules guarantee the basic service capabilities, and then extract and encapsulate the basic functions required by each business module, split out business services and public services, and support business capabilities.

The system splits the major parts of business activities into data centers and big…

What is Computer vision

Computer vision (CV) in a narrow sense is a simulation of biological vision using computers and related equipment, which can be simply understood as a substitute for “eyes.” Its main task is to obtain three-dimensional information of the corresponding scene by processing the collected pictures or videos, just like humans and many other kinds of creatures do every day.

Broadly speaking, it is a science of making decisions through the perception of image information such as two-dimensional and three-dimensional images and videos. These include computer science and engineering, signal processing, physics, applied mathematics and statistics, neuropsychology and cognitive science.

Main technical architecture

• Perception…

Augmented reality

Augmented reality refers to the superposition of virtual elements and reality (such as sound, two-dimensional and three-dimensional video images, etc.) formed by real-time calculation by a computer system.

It is a technology that uses sensors and display devices to augment the reality experience with digital pictures, sounds, and data. It is a cross-discipline of artificial intelligence and human-computer interaction, this technology calculates the position and angle of the camera image in real time and adds corresponding images, videos, and 3D models

The AR technology combine the virtual world displayed on the original screen with the real world to interact, blur…

Foundations

The foundation of machine learning is mathematics. Mathematics is not an optional theoretical method, but an indispensable pillar. If you are a computer engineer and use UML, ORM, design patterns and other software engineering tools/techniques every day, then please close your eyes for a second and forget everything. This is not to say that these concepts are unimportant, absolutely not! But machine learning requires a different approach. One of the reasons why Python is so popular today is its “prototyping speed.” In machine learning, a language that can model algorithms with a few lines of code is absolutely necessary.

Calculus…

Kubernetes is the embodiment of the philosophy of Cloud Native Computing. Through container technology and abstract IaaS interface, it shields the details and differences of the underlying infrastructure, and can realize multi-environment deployment and flexible migration between multiple environments, this way It can achieve cross-domain and multi-environment high-availability and multi-active disaster recovery. On the other hand, it helps users not to be bound by a cloud vendor or underlying environment.

On a global scale, in addition to major public clouds that have competed to support Kubernetes, Kubernetes has also been widely used in the Internet, finance, communications, energy, e-commerce, and…