Pandas
NumPy
Scikit-learn
OpenCV
Dataiku
Exploratory
htm.java
WEKA
Google Translate
DeepL Translator
Microsoft Translator
Mate Translate
Yandex.Translate
Crowdin
Linguee
GoldenDict
Pandas Google TranslatePandas is particularly recommended for data scientists, analysts, and engineers who need to perform data cleaning, transformation, and analysis as part of their work. It is also suitable for academics and researchers dealing with data in various formats and needing powerful tools for their data-driven research.
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Based on our record, Google Translate should be more popular than Pandas. It has been mentiond 510 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
Libraries for data science and deep learning that are always changing. - Source: dev.to / 30 days ago
# Read the content of nda.txt Try: Import os, types Import pandas as pd From botocore.client import Config Import ibm_boto3 Def __iter__(self): return 0 # @hidden_cell # The following code accesses a file in your IBM Cloud Object Storage. It includes your credentials. # You might want to remove those credentials before you share the notebook. Cos_client = ibm_boto3.client(service_name='s3', ... - Source: dev.to / about 2 months ago
As with any web scraping or data processing project, I had to write a fair amount of code to clean this up and shape it into a format I needed for further analysis. I used a combination of Pandas and regular expressions to clean it up (full code here). - Source: dev.to / about 2 months ago
Python’s Growth in Data Work and AI: Python continues to lead because of its easy-to-read style and the huge number of libraries available for tasks from data work to artificial intelligence. Tools like TensorFlow and PyTorch make it a must-have. Whether you’re experienced or just starting, Python’s clear style makes it a good choice for diving into machine learning. Actionable Tip: If you’re new to Python,... - Source: dev.to / 4 months ago
This tutorial provides a concise and foundational guide to exploring a dataset, specifically the Sample SuperStore dataset. This dataset, which appears to originate from a fictional e-commerce or online marketplace company's annual sales data, serves as an excellent example for learning and how to work with real-world data. The dataset includes a variety of data types, which demonstrate the full range of... - Source: dev.to / 9 months ago
> Maybe China can become the destination for ambitious smart people. Don't underestimate the language barrier. All those stereotypes about Chinese people mixing Rs and Ls? That works both ways, not just tongue twisters like Lion-Eating Poet in the Stone Den*, but even "Hello":... - Source: Hacker News / 1 day ago
Additionally, YouTube’s system supports multiple languages and is regularly updated to include new ones. This multilingual capability is made possible by training models on diverse datasets and leveraging translation technologies like Google Translate. - Source: dev.to / 29 days ago
20 years ago, in simpler times, people were sharing badly done human translations: https://archive.org/details/engrishtwotowerssubtitles And just plain mistakes: http://news.bbc.co.uk/2/hi/7702913.stm I've also encountered a case of real paid humans translating the English word "drake", in a mythological context where it was obviously a dragon, as if it were used in the sense of "male duck". Myself, I decided to... - Source: Hacker News / 2 months ago
As stated in the video, it translates to 'beach beast'. What I find remarkable is how difficult it seems for a lot of native English speakers to correctly pronounce the word. https://translate.google.com/?sl=nl&tl=en&text=strandbeest&op=translate. - Source: Hacker News / 6 months ago
*Automating Translation with Machine Translation Systems * Integrating machine translation can significantly speed up the localization process. Tools like Lingvanex, Google Translate, or DeepL offer APIs that enable instant translation. However, it’s not enough to simply “turn on” machine translation—you need to integrate it thoughtfully for maximum impact. - Source: dev.to / 6 months ago
NumPy - NumPy is the fundamental package for scientific computing with Python
DeepL Translator - DeepL Translator is a machine translator that currently supports 42 language combinations.
Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.
Microsoft Translator - Microsoft Translator is your door to a wider world.
OpenCV - OpenCV is the world's biggest computer vision library
Mate Translate - Ultimate translation app for Mac, iOS, Chrome and many more