Wherever you’re starting from, transforms enable you to get the most out of your data. Add context, content, and columns. Enrich it with outside data or generate text using templates or custom prompts. Your imagination is the only limit.
Convert audio files into text using the OpenAI Whisper third-party service.
Generate embeddings for text data using third-party LLMs (language models) such as OpenAI’s ada-2.
Clean the text in a specific column of a dataset.
Generate text guided by a Prompt Template.
Turn a single line of CSV data into a structured dataset with individual columns.
Summarize text using an LLM model and a prompt template.
Mantium adds value to existing data by providing additional information or context, such as adding tags, labels, or categories to data, or by creating summaries.
Transformation
Turns a single line of CSV data into a structured dataset with individual columns.
Transformation
Reformat CSV is used to reformat the CSV content with a different delimiter.
Transformation
Used to split text into smaller chunks so that each chunk is small enough for an AI model to process.
Transformation
Create a new column in a dataset based on existing column(s) and a specified function or formula.
Enrichment
Produce a shorter version of a cell while preserving its important information.
Enrichment
Extract functions from .py files.
Enrichment
Extract specific patterns from text data using regular expressions.
Enrichment
Convert categorical data into numerical values for machine learning models.
Enrichment
Standardize the scale of numeric features in a dataset to improve the performance of machine learning algorithms.
Enrichment
Identify and remove duplicate records from a dataset.
Enrichment
Convert date and time information into a standardized format.
Enrichment
Fill in missing values in a dataset using various techniques such as mean, median, or mode.
Transformation
Combine two or more datasets based on common columns or keys.
Enrichment
Identify unusual or suspicious patterns in data that deviate from the norm.
Enrichment
Convert addresses or location data into geographic coordinates (latitude and longitude).
Enrichment
Categorize text data into predefined groups or classes.
Enrichment
Identify and extract relevant keywords from text data.
Enrichment
Identify and group documents or text data based on the topics they contain.
Enrichment
Extract entities such as names, organizations, dates, and locations from the text.
Enrichment
Identify the language of the text data automatically.
Enrichment
Analyze the sentiment of text data to categorize it as positive, negative, or neutral.