Unlock the Power of Data Predictions with Obviously AI: Step-by-Step Guide

Unlock the Power of Data Predictions with Obviously AI: Step-by-Step Guide

Table of Contents:

1. Introduction
2. Getting Started with Obviously.ai
3. Selecting a Data Set
4. Making Predictions
5. Analyzing the Data
   • 5.1 Drivers for Predicting Potential
     • 5.1.1 Wage and Potential
     • 5.1.2 Overall Rating and Potential
     • 5.1.3 Age and Potential
     • 5.1.4 Preferred Foot and Potential
     • 5.1.5 Skill Moves and Potential
   • 5.2 Top Drivers by Impact
6. Building Personas
7. Exporting Data
8. Technical Specifications
9. Conclusion

Introduction In this article, we will explore how to make data predictions using Obviously.ai, a powerful AI-driven tool for data science. We will be working with a sample data set of FIFA players to demonstrate the capabilities of this tool.

Getting Started with Obviously.ai To begin, you need to sign up for an account at Obviously.ai. They offer a free plan for beginners, but do note that you must have a company email address to use the tool. If you don't have one, you can use a service like Email on Deck to create a disposable email for signing up.

Selecting a Data Set Once you have logged into your Obviously.ai account, the first step is to select a data set to work with. You can either upload your own CSV file or use the sample data sets provided by Obviously.ai. In this project, we will be using the FIFA Players data set, which is clean and contains all the necessary data for our analysis.

Making Predictions After selecting the data set, the next step is to pick a column to predict. In this case, we will be running a prediction on the "potential" column of the FIFA Players data set. Once you have made your selection, simply click "go" and then "start predicting." The time taken for Obviously.ai to make predictions will depend on the size of the data set.

Analyzing the Data Once the predictions are ready, we can start analyzing the data. The "drivers" section provides insights into what factors are inversely or directly proportional to the potential of FIFA players. We can observe that wage has no impact on potential, but the overall rating and age are directly proportional to it. Similarly, we can explore the impact of preferred foot and skill moves on potential.

Top Drivers by Impact The "top drivers by impact" section allows us to delve deeper into the analysis. For example, we can see how age affects the potential of FIFA players. As players grow older, their potential declines. We can also analyze the impact of preferred foot on potential. Players with a preferred left foot tend to have slightly higher potential. Moreover, skill moves also play a role in determining potential, with players having more skill moves exhibiting a better predicted potential.

Building Personas In the "personas" tab, we have the opportunity to create personas and predict further outcomes. This feature is useful for understanding how potential is influenced by specific attributes. By specifying certain characteristics, we can gain deeper insights into the impact of potential.

Exporting Data Obviously.ai provides an "export" tab that allows us to export the analyzed data for use in other applications or further analysis. This feature enables easy integration with other tools in your data pipeline.

Technical Specifications The "tech specs" tab provides a bird's-eye view of the data set and includes information such as the columns used. It aids in understanding the overall structure and composition of the data set.

Conclusion In conclusion, Obviously.ai has made data analysis and prediction more accessible with its powerful AI-driven tool. By utilizing the functionalities such as drivers, personas, and exporting data, users can gain valuable insights from their data sets. This no-code project demonstrates the ease of use and effectiveness of Obviously.ai in making predictions and analyzing data.

Article: Making Data Predictions with Obviously.ai

In this article, we will explore how to make data predictions using Obviously.ai, a powerful AI-driven tool for data science. The tool provided by Obviously.ai allows users to create predictions on a sample data set of FIFA players. Let's dive into the step-by-step process to make accurate predictions and analyze the data.

Introduction

Predictive analytics has become an integral part of decision-making processes in various industries. With Obviously.ai, users can harness the power of AI and machine learning algorithms to make accurate data predictions.

Getting Started with Obviously.ai

To get started with Obviously.ai, you need to sign up for an account. The platform offers a free plan for beginners, making it accessible to individuals who are just getting started with data analysis. However, it is important to note that a company email address is required to use Obviously.ai. If you don't have one, you can use a service like Email on Deck to create a temporary email address for signing up.

Selecting a Data Set

Once you have logged into your Obviously.ai account, the first step is to select a data set to work with. You have the option to either upload your own CSV file or use one of the sample data sets provided by Obviously.ai. For this project, we will be using the "FIFA Players" data set, which contains clean and Relevant data for our analysis.

Making Predictions

After selecting the desired data set, the next step is to choose a column to predict. In this case, we will focus on predicting the "potential" of FIFA players. Simply click "go" to start the prediction process. The time required for Obviously.ai to make predictions depends on the size of the data set you are working with.

Analyzing the Data

Once the predictions are complete, we can begin analyzing the data. The "drivers" section provides insights into the factors that affect the potential of FIFA players. For example, we can observe that the overall rating and age of players have a direct impact on their potential. Wage, on the other HAND, does not have any significant influence on potential. This analysis allows us to understand the key drivers of potential in FIFA players.

Top Drivers by Impact

The "top drivers by impact" section allows us to dig deeper into the analysis. We can explore the impact of specific factors such as age, preferred foot, and skill moves on potential. For instance, older players tend to have lower potential, while those with a preferred left foot have slightly higher potential. Additionally, players with more skill moves exhibit a better predicted potential. These insights provide a comprehensive understanding of the various factors that contribute to a player's potential.

Building Personas

In the "personas" tab, users can create personas to predict further outcomes. This feature is particularly useful for understanding how potential is influenced by specific attributes. By defining characteristics such as age, preferred foot, and skill moves, users can gain deeper insights into how potential varies among different player profiles.

Exporting Data

Obviously.ai provides an "export" tab that allows users to export the analyzed data for use in other applications or for additional analysis. This feature facilitates seamless integration with other tools in your data pipeline, enabling further exploration and visualization of the data.

Technical Specifications

The "tech specs" tab provides a comprehensive overview of the data set used for analysis. It includes information on the columns utilized and the structure of the data. This overview enables users to understand the composition of the data set and make informed decisions based on the technical specifications.

Conclusion

Obviously.ai simplifies the process of making data predictions and analyzing complex data sets. With its no-code interface and powerful AI capabilities, the tool empowers users to gain valuable insights and make informed decisions. Whether you are a beginner or an experienced data analyst, Obviously.ai provides a user-friendly platform for accurate predictions and data analysis.