不秃头的老陈

It's been a long time since I posted in the square.
Recently, I made a new AI framework, allowing AGI to complete transactions autonomously.
Currently, the win rate is 70%.
The trading strategy is conservative.
#比特币流动性 #ETH走势分析 #加密市场观察

Only 2 giant whales have sold, panic selling

AI large model technology, looking for a boss, looking for a position

#加密市场反弹 Delicious

Recently developing event quantification, anyone interested can join in.

Significant reduction equals going long

Face Fitting + Virtual Camera Three Color Light

#ALPHA Share it again,
The so-called facial recognition can be divided into two parts:
The first part is the fusion overfitting of KYC face and real human face.
The second part is tricolor light verification.
If you don't understand, you can comment.
Receiving various tools selenium scripts.

Today's technical sharing is: selenium script
Can't sleep and the boss happens to ask me to do software, I feel like sharing a bit.
For those who are working on scraping, manual scraping has always been a headache. Simple projects are manageable, but complex ones can be quite troublesome. Using ads synchronization makes you fear being targeted, so what to do? Don't panic, there's selenium,
It's a simulation framework that can simulate your operations by capturing the HTML page tags for recognition and clicking.
Different strategies can be formulated based on different requirements to free your hands,
Later, I will teach everyone how to create a simple script.
Follow me for more technical content.
#撸毛 #撸毛教程 #alpha

I saw something that mentioned facial KYC. To put it simply, the technical barrier lies in the three-color face, but Binance's is not top-tier, so it can use fitted faces. Those with capable technology can give it a try...

Three-color Dribbling Face Just Researched

Yes, doing it

Quantification is not a strategy, but a combination; multiple strategies respond to one cycle.

How to do quantitative analysis well? Taking BTC as an example, ordinary people look at candlestick charts, smart people look at news, while technology needs to observe multiple dimensions. In addition to candlestick charts and news, it is also necessary to monitor institutional wallet flows, the movements of whales, and effectively use models to analyze trends, etc.
The road to quantitative analysis is long and arduous.

In this circle, the house earns 50, those who understand the technology earn 30, and the remaining 20 is for the public

The implementation method is either to capture packets and use APIs or to simulate with Selenium; you can directly use AI to create some technology.

Why not work with me? I have a financial quantitative framework model. If a boss wants to invest, they can contact me.

A one-sided market can only use overbought or oversold strategies; the rest are basically dead.

It seems that the position cannot be withdrawn.

Let's update how to train an intelligent agent. I will break it down into several tweets to teach you step by step how to use deepseek. First, choose the right model; here I am using Yuanbao as an example (Tencent, remember to pay me for the advertisement). Next, I will explain the role of prompt programming. You can think of AI as a hundred thousand whys. If you don't specify the scope of its responses, it will answer you randomly. Prompt programming is used to regulate its response scope and thinking logic. Here I use a simple prompt programming example: You need to define the role the AI will play: for instance, let it act as a very impressive cryptocurrency trader. This way, it will adopt this role and help you answer questions with knowledge about cryptocurrencies. The second step is to ensure that it learns all about candlestick chart knowledge so that it can understand candlesticks. The third step is to specify what you want it to help you with: for example, based on the indicators I provide, help me predict the system's trend for the next few minutes or days. The fourth step is to make it speak in human language, so you can get a preliminary intelligent agent prototype. At this point, the agent can only be considered to have a rough framework; further fine-tuning is needed, and later I will also teach everyone how to train their own intelligent agents. I am still that Mo Chen; follow me for more knowledge in the AI field. Friends are welcome to discuss together; I will answer any technical questions you have.