Course 2672
Course Introduction:Golang has an in-depth understanding of the GPM scheduler model and full scenario analysis. I hope you will gain something from watching this video; it includes the origin and analysis of the scheduler, an introduction to the GMP model, and a summary of 11 scenarios.
Course 88220
Course Introduction:"C Language Tutorial" C language is a general-purpose, procedural-oriented computer programming language. In 1972, Dennis Ritchie designed and developed the C language at Bell Telephone Laboratories in order to port and develop the UNIX operating system. C language is a widely used computer language that is as popular as the Java programming language and both are widely used among modern software programmers.
Course 16380
Course Introduction:This course will take you to truly understand C language and enter C language
Course 59730
Course Introduction:This course will take you into C language from scratch. The course content includes some basic knowledge of C language such as common Linux commands, C language constant variables, operator expressions, etc.
Course 25005
Course Introduction:Go is a new language, a concurrent, garbage-collected, fast-compiled language. It can compile a large Go program in a few seconds on a single computer. Go provides a model for software construction that makes dependency analysis easier and avoids most C-style include files and library headers. Go is a statically typed language, and its type system has no hierarchy. Therefore users do not need to spend time defining relationships between types, which feels more lightweight than typical object-oriented languages. Go is a completely garbage-collected language and provides basic support for concurrent execution and communication. By its design, Go is intended to provide a method for constructing system software on multi-core machines.
Best way to preload route data before accessing the route.
2023-11-17 14:54:42 0 2 379
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2023-11-14 12:58:58 0 1 292
Indirect modification of the overloaded attribute of App\Models\User::$profile is invalid.
2023-11-08 11:50:44 0 1 270
CSS collapsing margins: what is their purpose?
2023-10-25 19:38:51 0 1 221
Course Introduction:Large language models and word embedding models are two key concepts in natural language processing. They can both be applied to text analysis and generation, but the principles and application scenarios are different. Large-scale language models are mainly based on statistical and probabilistic models and are suitable for generating continuous text and semantic understanding. The word embedding model can capture the semantic relationship between words by mapping words to vector space, and is suitable for word meaning inference and text classification. 1. Word embedding model The word embedding model is a technology that processes text information by mapping words into a low-dimensional vector space. It converts words in a language into vector form so that computers can better understand and process text. Commonly used word embedding models include Word2Vec and GloVe. These models are widely used in natural language processing tasks
2024-01-23 comment 965
Course Introduction:Natural language processing (NLP) is a field of computer science that focuses on enabling computers to communicate effectively using natural language. Language models play a crucial role in NLP. They can learn probability distributions in language to perform various processing tasks on text, such as text generation, machine translation, and sentiment analysis. Types of Language Models There are two main types of language models: n-gram language model: considers the previous n words to predict the probability of the next word, n is called the order. Neural Language Model: Use neural networks to learn complex relationships in language. Language model in Python There are many libraries in Python that can implement language models, including: nltk.lm: provides the implementation of n-gram language model. ge
2024-03-21 comment 994
Course Introduction:Autoregressive language model is a natural language processing model based on statistical probability. It generates continuous text sequences by leveraging previous word sequences to predict the probability distribution of the next word. This model is very useful in natural language processing and is widely used in language generation, machine translation, speech recognition and other fields. By analyzing historical data, autoregressive language models are able to understand the laws and structure of language to generate text with coherence and semantic accuracy. It can not only be used to generate text, but also to predict the next word, providing useful information for subsequent text processing tasks. Therefore, autoregressive language models are an important and practical technique in natural language processing. 1. The concept of autoregressive model. The autoregressive model is a model that uses previous observations to
2024-01-22 comment 0 324
Course Introduction:According to news on February 25, Meta announced on Friday local time that it will launch a new large-scale language model based on artificial intelligence (AI) for the research community, joining Microsoft, Google and other companies stimulated by ChatGPT to join artificial intelligence. Intelligent competition. Meta's LLaMA is the abbreviation of "Large Language Model MetaAI" (LargeLanguageModelMetaAI), which is available under a non-commercial license to researchers and entities in government, community, and academia. The company will make the underlying code available to users, so they can tweak the model themselves and use it for research-related use cases. Meta stated that the model’s requirements for computing power
2023-04-14 comment 0 1313
Course Introduction:From security and privacy concerns to misinformation and bias, large language models come with risks and rewards. There have been incredible advances in artificial intelligence (AI) recently, largely due to advances in developing large language models. These are at the core of text and code generation tools such as ChatGPT, Bard, and GitHub’s Copilot. These models are being adopted across all sectors. But how they are created and used, and how they can be misused, remains a source of concern. Some countries have decided to take a drastic approach and temporarily ban specific large language models until appropriate regulations are in place. Here’s a look at some of the real-world adverse effects of large language model-based tools, and some strategies to mitigate them.
2023-05-12 comment 0 867