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The original address is here. What is word embedding? Word embedding is a series of natural language processing technologies aimed at mapping semantics to geometric space. This is done by associating a number vector with each word in the dictionary, so that the distance between any two vectors (such as L2 distance or more commonly cosine d ...

1, read_sql and to_sql function 1.1 read_sql function Reading data is generally read from the database, so in read_ Fill in the corresponding SQL statement in the SQL () function to read the data we wantpd.read_sql(sql, con, index_col=None, coerce_float=True, params=None, parse_dates=None, columns=None, chunksize=None) 1) sql: SQL command ...

Artificial intelligence learning is inseparable from the verification of practice. It is recommended that you can learn more in Flyai AI competition service platform Take part in more training and competitions to improve your ability. FlyAI is a one-stop service platform that provides AI developers with data competition and supports GPU offli ...

In order to define the mathematical expression more conveniently and describe the mathematical model more accurately, TF uses Tensor to represent all data uniformly. In the actual calculation formula, that is, the transformation process of the expression, the data in the expression corresponding to the model is carried by the Tensor. Provide ...

catalogue 1. Learning objectives 2. Operation explanation 3. Job results 1. Operation 1 2. Assignment 2 1. Learning objectives Using Python to achieve different investment ratiosUsing Python to implement mean variance model 2. Operation explanation Through the last task, you have learned something about Markowitz's mean variance ...

Hello, everyone. I've shared many articles about Pandas before. Today I'll share five small and beautiful practical cases of Pandas. My favorite partners, remember to collect, share and praise. The content is mainly divided into: How to simulate data by yourself Multiple data processing methods Data statistics and visualization User RFM m ...

The business scenario is multi label classification prediction. It is rumored that xgboost won the champion of most non xx data in the kaggle field, so it tried ox knife xgboost for the first time. xgboost model training reported an error. Baidu turned around and didn't find the corresponding solution. Finally, it tried out the solution by gues ...

First of all, what is Liuli? This is an open source project I recently developed. The main purpose is to enable friends with reading habits to quickly build a multi-source, clean and personalized reading environment.Why Liuli?Liuli was originally named 2C, and the friends of the communication group behind provided the name of Liuli, which is ta ...

Ex3_ Machine learning_ Wu Enda's course assignment (Python): multi class classification & Neural Networks instructions: This article is about Mr. Wu Enda's learning notes of the machine learning course on Coursera. The first part of this paper first introduces the knowledge review and key notes of the corresponding week of the c ...

[source code analysis] how Facebook trains super large models -- - (5) 0x00 summary As we mentioned earlier, Microsoft ZeRO can expand a trillion parameter model on 4096 NVIDIA A100 GPU s using 8-way model parallel, 64-way pipeline parallel and 8-way data parallel. FSDP (full sharded data parallel) is an upgraded version of PyTorch DDP propose ...