datascience - CybAI news

11 Aug

Understanding Your Data: The Essentials of Exploratory Data Analysis.

stp2y0 CommentsNewsbeginners, coding, community, datascience, development, engineering, inclusive, programming, python, software

What is EDA(Exploratory Data Analysis)? It refers to the critical process of performing initial investigations on data so as to discover patterns,to spot anomalies,to test hypothesis and to check assumptions with the help of summary statistics and graphical representations. EDA makes it easier for data scientists to find patterns, identify anomalies, test hypotheses, and verify assumptions by assisting in the best way to alter data sources to achieve the answers they require. EDA offers a better knowledge of data set variables and the interactions between them and is mainly used to examine what data might disclose beyond the formal modelling…

19 Jul

Supercharging LLMs: RoT Fuses Language Models with Decision Tree Search to Boost Reasoning Power

stp2y0 CommentsNewsai, beginners, coding, community, datascience, development, engineering, inclusive, machinelearning, software

This is a Plain English Papers summary of a research paper called Supercharging LLMs: RoT Fuses Language Models with Decision Tree Search to Boost Reasoning Power. If you like these kinds of analysis, you should join AImodels.fyi or follow me on Twitter. Overview This paper explores a novel approach called "Reflection on Search Trees" (RoT) to enhance the capabilities of large language models (LLMs). RoT involves integrating tree search methods with LLMs to improve their reasoning and decision-making abilities. The paper presents the design and evaluation of the RoT system, demonstrating its effectiveness in outperforming traditional LLMs on various tasks.…

19 Jul

Time Series in Data Science: Analysis of Bitcoin and Ethereum

stp2y0 CommentsNewscoding, community, cryptocurrency, datascience, development, engineering, inclusive, python, software, timeseries

Time series play a crucial role in Data Science, especially when analyzing financial data. The price variations of cryptocurrencies like Bitcoin and Ethereum offer an excellent opportunity to explore time series. In this article, we will analyze the price variations of Bitcoin and Ethereum in euros, using datasets ranging from 2012 to 2019 for Bitcoin and from 2015 to 2019 for Ethereum. We will also illustrate the use of some basic time series techniques with concrete examples and practical recommendations. Importing Libraries and Loading DataBefore diving into the analysis, we need to import the necessary libraries and load the datasets.…

17 Jul

Qwen2 Technical Report

stp2y0 CommentsNewsai, beginners, coding, community, datascience, development, engineering, inclusive, machinelearning, software

This is a Plain English Papers summary of a research paper called Qwen2 Technical Report. If you like these kinds of analysis, you should subscribe to the AImodels.fyi newsletter or follow me on Twitter. Overview The provided paper is a technical report on the Qwen2 audio model. It covers the model's tokenizer, architecture, and other key technical details. The report aims to provide a comprehensive overview of the Qwen2 system for researchers and developers. Plain English Explanation The Qwen2 Technical Report outlines the technical details of the Qwen2 audio model. Qwen2 is a powerful machine learning model designed for various…

10 Jul

How to Handle Secrets in Jupyter Notebooks

stp2y0 CommentsNewscoding, community, datascience, development, devops, engineering, inclusive, security, software

With the rise of big data and machine learning, project Jupyter is becoming increasingly popular among data scientists and machine learning engineers. Jupyter Notebooks, together with IPython, provide an interactive workflow for developing, visualizing data, and writing texts and documentation, all in a single place and stored as a single document. However, data science and machine learning projects often need to access third-party APIs, read data from a data store, or interact with cloud services. This means that, just like normal code, the code in Jupyter Notebooks also needs to use secrets and credentials. These notebooks are nothing more than…

09 Jul

Unlocking the Power of Data with Data Science & Advanced Analytics

stp2y0 CommentsNewsanalytics, cloud, coding, community, data, datascience, development, engineering, inclusive, software

In today's data-driven world, businesses are increasingly relying on data science and advanced analytics to make informed decisions, improve operations, and gain a competitive edge. The realm of data science encompasses a variety of techniques, tools, and methodologies that allow organizations to extract meaningful insights from raw data. When combined with advanced analytics, these capabilities become even more powerful, enabling businesses to predict trends, optimize processes, and personalize customer experiences. One company at the forefront of this transformation is Datametica. Data Science and Advanced Analytics: A Game Changer Data science and advanced analytics involve leveraging statistical models, machine learning algorithms,…

05 Jul

Conquering Your First Database: Essential SQL Queries for Newbies

stp2y0 CommentsNewscoding, community, datascience, development, engineering, inclusive, programming, python, software, sql

Congratulations! You've embarked on the exciting journey of learning SQL, the language that unlocks the secrets hidden within databases. Whether you're a budding data analyst, a curious developer, or simply someone who wants to wield the power of data, understanding SQL is a game-changer. This blog post serves as your essential guide to conquering your first database, equipping you with the fundamental SQL queries you'll need to navigate its terrain. Along the way, we'll explore how these skills can be leveraged in the fascinating world of data science (with a nudge towards exploring an SQL Data Science course!). Unveiling the…

03 Jul

CRISP-DM: The Essential Methodology for Structuring Your Data Science Projects

stp2y0 CommentsNewscoding, community, data, datascience, datastructures, development, engineering, inclusive, machinelearning, software

As with any IT project, Machine Learning projects need a framework. However, classical methodologies do not apply or apply very poorly to Data Science. Among the existing methodologies, CRISP-DM is the most commonly used and will be presented here. Several variants exist. Be careful, CRISP is a framework and not a rigid structure. The purpose of using a methodology is not to have a magic formula or to be limited. It mainly provides an idea of the progress and steps, as well as good practices to follow. CRISP-DM stands for "Cross Industry Standard Process for Data Mining." It is, therefore,…

18 Jun

cTop Python Libraries for Data Science in 2024

stp2y0 CommentsNewscoding, community, datascience, development, engineering, inclusive, python, software

Top Python Libraries for Data Science in 2024 https://www.reddit.com/r/DevArt/comments/1dijfiv/top_python_libraries_for_data_science_in_2024/ The landscape of data science is ever-evolving, and staying updated with the latest tools is crucial for any data scientist. Python continues to be the dominant language in the field, thanks to its robust ecosystem of libraries that streamline data analysis, machine learning, and deep learning tasks. Here's a look at the top Python libraries for data science in 2024. 1. Pandas Pandas remains a cornerstone for data manipulation and analysis. Its DataFrame object allows for efficient handling of large datasets, and recent updates have improved performance and usability. In 2024,…

14 Jun

FastAPI for Data Applications: From Concept to Creation. Part I

stp2y0 CommentsNewscoding, community, dataengineering, datascience, development, engineering, fastapi, inclusive, llmops, software

In this blog post, we'll explore how to create an API using FastAPI, a modern Python framework designed for building APIs with high performance. We will create a simple API that allows users to add, update, and query items stored temporarily in memory. Alongside this, we'll discuss how you can extend this example to expose machine learning models, perform online processing in decision engines, and ensure best practices for a robust, secure API. Pre-requisites: Installation of FastAPI and Uvicorn Before diving into the code, we need to install FastAPI and Uvicorn, an ASGI server to run our application. Run the…