Nand Kishor is the Product Manager of House of Bots. After finishing his studies in computer science, he ideated & re-launched Real Estate Business Intelligence Tool, where he created one of the leading Business Intelligence Tool for property price analysis in 2012. He also writes, research and sharing knowledge about Artificial Intelligence (AI), Machine Learning (ML), Data Science, Big Data, Python Language etc... ...
Full BioNand Kishor is the Product Manager of House of Bots. After finishing his studies in computer science, he ideated & re-launched Real Estate Business Intelligence Tool, where he created one of the leading Business Intelligence Tool for property price analysis in 2012. He also writes, research and sharing knowledge about Artificial Intelligence (AI), Machine Learning (ML), Data Science, Big Data, Python Language etc...
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The Difference Between Deep Learning & Machine Learning You must know!


- While feeding raw data in machine learning doesn't work, deep neural networks do not require manual feature engineering. Instead, it learns on its own by processing and learning the high-level features from raw data
- Deep Learning's self-learning capabilities mean higher accuracy of results and faster processing. Since machine learning requires manual intervention, this results in decreased accuracy and can lead to human error during the programming process
- DL can learn high-level, non-linear features necessary for accurate classification. For example, if one uses traditional machine learning algorithms for computer vision problem, you would need time to extract the important features from hundreds of images. In Deep Learning, one can feed raw pixels to process images and correctly classify objects in images with higher accuracy