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Data Analytics News
Medium
2w
12
How Bayesian Deep Learning works part5
- Deep learning has improved predictive maintenance in estimating the remaining useful life of physical systems.
- Bayesian neural networks provide confidence intervals around the predictions, addressing the uncertainty inherent to the estimates.
- Stein variational gradient descent is a powerful algorithm for training Bayesian deep learning models, outperforming other techniques in terms of convergence speed and predictive performance.
- Bayesian deep learning can enhance performance by utilizing uncertainty information provided by the models.
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Medium
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Predicting Breast Cancer Diagnoses
- The Breast Cancer Coimbra dataset from the UCI Machine Learning Repository was used along with a synthetic dataset from Kaggle.
- Data preprocessing, exploratory data analysis (EDA), and model fitting were conducted on the datasets.
- The synthetic dataset exhibited different distributions and lower correlations compared to the original dataset.
- The KNN model performed the best among the evaluated models based on various metrics.
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Decoding Stress: A Data-Driven Journey
- Before starting the investigation, the data needs to be prepared by fixing mistakes and converting words into numbers.
- The data is split into a training set and a testing set to train the models and evaluate their performance.
- The MinMaxScaler tool is used to ensure fair analysis and balance the features.
- The best model, ExtraTreesClassifier, is chosen for accurate predictions and trained models are saved using Pickle.
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Great Gamified SQL Courses for Beginners
- SQL Murder mystery is a fun themed puzzle game for beginners to navigate.
- SQLPD is a crime-themed game with small tasks and a charming UI, but it's paid on license.
- SQL Island is a non crime-themed game with cute storylines, great for younger learners.
- Coding Bat is a free algorithm game recommended by the author.
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Medium
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Bhavya’s Success Story: A Testament to Strategic Upskilling in Supply Chain Management, the final…
- Bhavya's success story showcases the importance of strategic upskilling in supply chain management.
- Her expertise in data analysis and proficiency with AI tools positioned her as a standout candidate.
- Bhavya's ability to leverage AI to enhance productivity aligned with strategic goals.
- Her practical projects and hands-on experiences predict continuous growth and innovation.
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Pymnts
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Data Revolution Adds Stability to Uncertain Financial Transactions
- Data analytics and AI have significantly transformed the card payments industry, reshaping how transactions are processed, enhancing security, and improving customer experience.
- Data analytics and AI have enabled enhanced fraud detection and security measures, reducing false positives and minimizing fraud losses.
- Data analytics allows for personalized customer experiences by tailoring offers and communications based on customer preferences and behaviors.
- Data analytics and AI streamline operations in the card payments industry, automating transaction approval processes and improving operational efficiency.
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Medium
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Iris Species Report
- Data analysis helps understand what the data is trying to tell and make informed decisions based on that understanding.
- The correlation coefficient measures the strength and direction of a relationship between two variables.
- K-means clustering analysis on the iris dataset revealed well-defined clusters and meaningful patterns.
- Further refinement and improvement may be possible in the clustering performance.
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Medium
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Executive Summary
- Software export is a critical component of international trade, driving economic growth and innovation globally.
- The report utilizes data visualization techniques to present insights into the software export sector using Streamlit and Matplotlib.
- Exploratory Data Analysis (EDA) on software houses in Pakistan in 2024 involves examining various aspects to gain insights into the distribution, size, industry focus, technological expertise, revenue, growth, employee skills, clientele, challenges, and opportunities within the sector.
- Software exports are integral to global economic growth and innovation. In Pakistan, they offer avenues for economic diversification, job creation, and technological advancement.
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Creating a scenario for the complete hacking of a bank's sensitive systems and data involves a…
- Exploiting Vulnerabilities: Hackers identify and exploit vulnerabilities in the bank's network infrastructure or software.
- Privilege Escalation: Hackers gain access to sensitive systems by escalating their privileges.
- Data Theft: Hackers exfiltrate sensitive data, including customer financial information and account credentials.
- Disruption of Services: Hackers may launch DDoS attacks, disrupting access to the bank's services.
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Medium
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ETL vs ELT: Choosing the Right Data Integration
- ETL (Extract, Transform, Load) vs ELT (Extract, Load, Transform) are two common approaches in data integration, differing in the order of data transformation and loading.
- This blog discusses the key differences between ETL and ELT and helps you determine which approach is best suited for your specific data integration needs.
- Understanding the functionalities, advantages, and drawbacks of ETL and ELT empowers you to choose the optimal approach for your data landscape.
- Both ETL and ELT serve the critical function of integrating data, but their workflows differ significantly.
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Medium
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What is ELT & How Does It Work?
- ELT is a data integration methodology that prioritizes quickly bringing data into a central location for later transformation.
- ELT involves three key stages: extraction, loading, and transformation.
- In ELT, data is directly loaded into a target system, such as a data lake or data warehouse, without extensive upfront transformation.
- Once the data is loaded, the transformation stage begins, where data is cleaned, standardized, and transformed for analysis.
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Python — Part 1
- Python supports several built-in data types, each with its own characteristics and use cases.
- Some commonly used data types in Python include integers, floating-point numbers, strings, booleans, lists, tuples, dictionaries, sets, and NoneType.
- Python strings can be accessed using indexing and slicing, and string formatting allows for creating formatted strings by replacing placeholders with variable values.
- String formatting methods in Python include the % operator, the .format() method, and f-strings (formatted string literals).
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WANs: Orchestrating Data Engineering Evolution Quietly
- WANs revolutionize data sharing across geographic locations.
- WANs are essential for cloud computing and data ecosystem.
- Legacy time-sharing processing influences modern data pipelines.
- WANs enable real-time data processing and orchestration.
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Medium
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Introduction to Hypothesis Testing in Data Analysis
- Hypothesis testing is a fundamental concept in statistics and data analysis that allows us to make inferences about population parameters based on sample data.
- Hypothesis testing involves formulating two competing hypotheses — the null hypothesis (H 0) and the alternative hypothesis (H 1) — and using sample data to determine which hypothesis is supported by the evidence.
- There are several types of hypothesis tests, each suited to different scenarios and research questions.
- Hypothesis testing finds applications across various domains, including evaluating the effectiveness of interventions, comparing group means, and exploring relationships between variables.
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Medium
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Data Analysis Mindset Module One: Basic Skills of Data Analysis Thinking(2)
- Structured thinking is a tool for analyzing problems in a more rational and thorough manner.
- Systematic thinking provides unexpected insights when structured thinking seems blocked.
- Common mistake analysts make is focusing on analysis without actionable conclusions.
- Business objective is to influence user actions by interpreting data and providing practical recommendations.
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