Obviously AI

A user-friendly no-code AI platform enables creation and deployment of data science models, eliminating the need for coding.

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What is Obviously AI?

Obviously AI is a tool that uses no coding and is based on Artificial Intelligence. It lets users quickly build and put into action data science models without needing to write any code. It offers a simple way to run data science tasks with just one click, including making machine learning algorithms, explaining the results, and predicting what might happen next. With Obviously AI, users can change raw data into top-notch predictive models in just a few minutes, rather than taking several months.

How to use Obviously AI?

To get started with Obviously AI, follow these easy steps: 1. Register on the Obviously AI website to create an account. 2. Import your data in a table format and pick the main variable you want to focus on. 3. Decide what kind of prediction model you want to build - it could be for classification, regression, or time series forecasting. 4. Press the 'Build Model' button to create an AI model based on the data you provided. 5. Check out the results and predictions from the model to see how it performed. 6. If needed, deploy the model with just one click to create web applications or connect it to your existing tools using real-time REST APIs.

Features

Create AI models quickly in just a few minutes

Use Cases

Predicting Customer Churn
Lead conversion prediction
Predicting Loan Repayment
Deception Identification
Forecasting Sales
Predicting Prices Dynamically
Crop Yield Forecast
Deal size prediction
Forecasting of sales during a particular timeframe
Predicting stock prices for the following day.

Frequently Asked Questions

Clearly, Obviously AI is a no-code AI tool enabling users to quickly create and launch data science models without requiring any coding skills. It offers a simple one-click solution to manage data science processes, including creating machine learning algorithms, interpreting results, and forecasting outcomes. Using Obviously AI, users can transform raw data into top-tier predictive models in a matter of minutes, rather than taking months.

To start using Obviously AI, follow these simple steps: 1. Register on the Obviously AI website to get started. 2. Import your data in a table format and pick the main variable you want to focus on. 3. Decide what kind of prediction model you want to build - it can be classification, regression, or time series. 4. Click the 'Build Model' button to create an AI model based on your data. 5. Look at the results and predictions from the model to understand what it says. 6. If you want, deploy the model with just one click to create web apps or connect it to your existing tools using real-time REST APIs.

Obviously AI is a no-code AI tool that enables users to quickly create and implement data science models without needing to write code. It offers a one-click solution for executing data science tasks, including developing machine learning algorithms, interpreting results, and forecasting outcomes.

To get started with Obviously AI, create an account on the website, then upload your data in a table format. Next, pick the target variable you want to focus on. After that, choose the type of prediction model that suits your needs. Click the 'Build Model' button to proceed. Check out the results and predictions from the model. If you're satisfied, you can deploy the model instantly with just one click. Alternatively, you can integrate it into your existing tools using real-time REST APIs.

Obviously AI's key features include creating AI models quickly, deploying them to production with a single click, and automating model monitoring with custom if-this-then-that actions. It also offers real-time REST APIs for seamless integration and sharing. Additionally, users have 24x7 access to a dedicated expert data scientist for support.

Obviously AI has various practical applications, including forecasting customer turnover, anticipating lead conversion, predicting loan repayment, identifying potential fraud, estimating sales, predicting dynamic pricing, forecasting yields, estimating deal sizes, and making predictions about time series data such as sales during a specific period or stock prices for the next day.

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