Some perks of using Deep Learning:
- Utilization of Unstructured Data
Not all data are accurately structured to be trained on, conversely, they are mostly unstructured and exist in different format types. Traditional Machine Learning systems are not as effective as deep learning ones in the utilization of various formats. Using neural networks allow Deep Learning to reveal any existing relations between various data types, for instance, social media chatters, company reports, and industry analysis.
- No Need for Feature Engineering
Deep Learning is able to create new features on its own. Previously companies always needed a data scientist to perform feature engineering, the process of extracting features from raw data to better understand occurred problems. With the help of Deep Learning, software systems can effectively find patterns that correlate and combine them to enable faster learning without explicitly being programmed.
- No Need for Data Labeling
Most innovative applications depend on labelled data. Data Labeling, the process of the manual curation of data, can be expensive and time-consuming. Applying Deep Learning, companies do not need to spend their resources on labelling data, as Deep Learning does this in a fully automated way.
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