Infographics

Break down complex data science topics into easy-to-remember bits with the most thorough and informative infographics.

Navigate your way through the sea of weighty data science content with the help of our 365 Data Science infographics and make your learning experience much simpler and more memorable.

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Gradient Descent Infographic

Our Gradient Descent Infographic provides an in-depth overview of an essential method widely applied in machine learning. What is Gradient Descent? Gradient Descent is an optimization algorithm that finds the local minimum of a function. It’s used in machine learning for cost function minimization. Gradient descent is essential to various machine learning models used by data scientists and machine and deep learning engineers. The infographic offers a well-rounded definition of gradient descent, machine learning applications, and the method's intuition. It further outlines the step-by-step process of the gradient descent algorithm—starting with initial coefficient values and repeating the process until converging on a minimum. The infographic also highlights the gradient descent assumptions and compares the pros and cons of stochastic gradient descent—a variant that updates the coefficients more frequently.

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Regularization Infographic

Our regularization infographic provides a comprehensive overview of an essential machine-learning technique. Regularization is a technique that helps prevent models from overfitting by introducing constraints into the loss function. For instance, in logistic regression, regularization techniques can be used to optimize the model's performance. The infographic provides a clear, concise definition of regularization, highlighting its role in balancing overfitting and underfitting. It illustrates how adding noise and improving generalization enhance model performance on new data. It also gives in-depth look at various regularization methods, including L1 regularization (Lasso regularization) and L2 regularization (Ridge regularization). It explains their formulas and how they influence coefficient adjustment in model training. Additionally, the infographic explores Elastic Net, a method blending Ridge and Lasso regularization, along with a 2-stage regularization process.

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Logistic Regression Infographic

This logistic regression infographic provides a clear and comprehensive overview of a standard statistical method used to predict binary outcomes. Unlike simple linear regression, logistic regression excels at deciphering the connection between multiple independent variables and one dependent variable. It simplifies the comprehension of intricate data relationships, making it a perfect gateway to machine learning. Logistic regression handles non-linear relationships effectively, delivering robust results without intricate hyperparameter adjustments.

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Linear Regression Infographic

This Linear Regression infographic demystifies the principles behind a standard statistical model used in machine learning—showing how to predict and understand linear variable relationships. It depicts its mathematical formula, training process, and practical applications with examples. Are you struggling to recall the linear regression assumptions? Unsure when to apply linear regression in machine learning? Download our infographic for an instant cheat sheet.

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ABCs of AI and Deep Learning

Artificial intelligence is a trending topic that intrigues and perplexes. But what is it, and how does it work? Our comprehensive ABCs of AI and Deep Learning Infographic introduces you to the basics of artificial intelligence through its deep learning foundations.   Arranged alphabetically, this glossary provides an overview of essential terms and phrases that define deep learning and AI concepts. Each letter of the alphabet represents methodologies, such as convolutional neural networks, natural language processing, and Xavier initialization.   Use the ABCs of AI and Deep Learning Infographic to foster your curiosity and navigate the complexities of these transformative technologies. 

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How to Become a Research Analyst

The research analyst is an entry-level position that is responsible for helping a company coordinate its research related activities and investigate special requests. They serve as task leads across the departments within a company, coordinating between stakeholders, project teams, master data teams and team leaders. The dynamic and responsible nature of the job gives the necessary experience for individuals to grow into future analytics managers and data scientists. Therefore, in this free pdf infographic on How to Become a Research Analyst, we are going to describe the research analyst profile, job responsibilities, average salary numbers, required skills and more, so you can start on the right foot.

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How to Become a Business Analyst

The business analyst is one of the most dynamic roles in a company, as they are tasked with the responsibility to bridge the organization’s information technology capabilities with its business goals. Combined with a high-paying salary and room for career growth , the position is a highly desired career by many business professionals. Therefore, we have created this free pdf infographic that is going to cover what does a business analyst do, salary information, business analyst skills requirements and career path to show you what to expect and decide for yourself if this is the right career for you.

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How to Become a Data Analyst Intern

In the highly competitive data science job market, data analyst internships are a perfect way for you to gain hands-on experience working with data to answer critical business questions, learn important soft skills and expand your networking circle for career growth. The 365 Data Science Data Analyst Intern infographic will show you how to get a data analyst internship by going over the position responsibilities, the required technical skills and educational background for the data analyst position.

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World of Supervised Machine Learning

Тhe introduction of Artificial Intelligence and its subset Machine Learning have introduced a whole new paradigm of possibilities in the realm of data related activities. In this visually beautiful World of Supervised Machine Learning infographic, we are giving essential information on all the different types of supervised machine learning, starting from the least complex - Linear Regression, to the most complex- XGBoost. Some of the things you will learn in this free pdf infographic are the advantages and disadvantages of each type, their algorithm speed, preprocessing, starter datasets and areas of application.

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The 365 Data Science All In One Infographic

Data science is a relatively new field that combines various disciplines like mathematics, statistics, machine learning, data analytics and programming, which is why coming to a universal definition and understanding of this ever growing field is quite the challenge. Despite that, the 365 Data Science Team has united their efforts to create a comprehensive overview of the data science field. This free 365 Data Science pdf infographic covers the types of data, the associated data techniques, the data related professions, places of application and more, giving you a holistic picture of data science.

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