Data Science

Here you’ll find all articles related concepts and tools in data science, whether its Python tutorials or conceptual articles.

Data science revolves around the study of data. It encompasses various techniques and technologies for collecting, storing, analyzing, and visualizing data. Data science and machine learning are disciplines that are closely related. Both fields involve working with data and using it to make predictions or decisions. However, while data science is a broad field encompassing many techniques and technologies, machine learning focuses on developing and applying algorithms that can learn from data and make predictions or decisions. Machine learning is thus also considered a subfield of data science. In practice, the two disciplines have substantial overlap. They both use algorithms to analyze and make predictions from data. And both fields use other techniques, such as data visualization and statistical analysis, to explore and understand the data.

Data science has inspired the job of the “data scientist,” which plays an important role in many organizations. Data scientists often work with large volumes of structured and unstructured data, and they use a variety of tools and techniques to clean, transform, and analyze this data. This can include using machine learning algorithms, statistical modeling, and visualization techniques to uncover insights and predict future trends and behavior. This way, data scientists help organizations make better decisions and gain a competitive edge by leveraging their data assets.

Mastering Multivariate Stock Market Prediction with Python: A Guide to Effective Feature Engineering Techniques

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Are you interested in learning how multivariate forecasting models can enhance the accuracy of stock market predictions? Look no further! While traditional time series data provides valuable insights into historical trends, multivariate forecasting models utilize additional features to identify patterns and predict future price movements. This process, known as “feature engineering,” is a crucial step … Read more

Classifying Purchase Intention of Online Shoppers with Python

Customer Purchase Intention Prediction Python Machine Learning

Online shopping has become a part of our daily lives, and online stores are continually seeking to improve their sales. One way to achieve this is by using machine learning to predict customers’ purchase intentions. This innovative process can help businesses understand their customers’ behavior and tailor their marketing strategies accordingly. In this article, we … Read more

Measuring Regression Errors with Python

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Evaluating performance is a crucial step in developing regression models. Because regression models return continuous outputs, such models allow for different gradations of right or wrong. Therefore, we measure the deviation between predictions and actual values in numerical terms. However, a universal metric to measure the performance of regression models does not exist. Instead, there … Read more

Rolling Time Series Forecasting: Creating a Multi-Step Prediction for a Rising Sine Curve using Neural Networks in Python

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Many time forecasting problems can be solved by predicting just one step into the future. However, some problems require a forecast for an extended period of time, which calls for a multi-step time series forecasting approach. This approach involves modeling the distribution of future values of a signal over a prediction horizon. In this article, … Read more

Geographic Heat Maps with GeoPandas: Visualizing COVID-19 Data in Python

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The spreading of COVID-19 has led to an increased interest in displaying region and country-specific information on geographic heat maps. Geographic heat maps use color shadings to visualize data that includes a spatial component and refers, for example, to countries, cities, towns, mountains, etc. The color shades are defined in a color palette and determined … Read more

Correlation Matrix in Python: How Correlated are COVID-19 Cases and Different Financial Assets?

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Correlation analysis is a powerful tool in financial market analysis, helping investors to better understand the interdependence of different assets. But what happens when an unprecedented global pandemic like COVID-19 shakes up the market? In this tutorial, we will show you how to create a correlation matrix in Python that will help you visualize the … Read more

Stock Market Prediction using Univariate Recurrent Neural Networks (RNN) with Python

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Financial analysts have long been fascinated by the prospect of predicting the prices of financial assets. In recent years, there has been increasing interest in using machine learning and deep learning techniques to generate predictions, in addition to traditional methods such as technical and fundamental analysis. Python libraries like Keras and Scikit-Learn make it relatively … Read more

Accessing Remote Data Sources via REST APIs in Python

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REST APIs provide straightforward access to remote data sources. Data scientists should learn about REST APIs because APIs (Application Programming Interfaces) are an important way for data scientists to access data from other sources. By using REST APIs, data scientists can access data from a wide range of sources, including databases, web services, and other … Read more

Getting Started with the Anaconda Python Environment for Machine Learning

Anaconda is a popular open-source Python environment specifically designed for data science and machine learning. It comes with a range of useful features and tools, including Jupyter Notebooks, pre-installed packages, and a powerful package manager. It is the most widely used Python environment among data scientists and machine learning practitioners. In this article, we will … Read more