Which is the best application of data science?

Data science has relevance in almost all fields of businesses starting from the banking sector, to healthcare to retail and even agricultural sector as well. A few of the best applications of data science (as per survey performed by Edureka) are risk analysis & fraud detection which is one of the most important use-cases in the BFSI sector, search engine optimization, designing custom and targeted campaigns for marketing, devising recommendation engines which is extensively practiced in Netflix etc.
Data science are also applied in speech recognition, traffic management, designing optimal routing plan for air traffic, and many more.

Machine learning is used in a large range of applications. The most well-known instances of machine learning in action is the recommendation engine that drives Facebook’s news feed. Facebook uses machine learning to modify how each member’s feed is delivered. If a member views a group’s posts frequently, the recommendation engine will start prioritising that group’s activity in the feed.

  1. The administration of customer relationships is referred to as customer relationship management. CRM software may use machine learning models to analyse email and encourage salespeople to respond to the most important emails first. Advanced systems can even give suggestions for prospective solutions that would be advantageous.

  2. Business intelligence is a type of intelligence that is used to help companies make better decisions. BI and analytics software vendors utilise machine learning to find potentially valuable data points, patterns of data points, and anomalies.

  3. Human resource information systems. Machine learning models can be used by HRIS systems to sort through applications and find the best candidates for available positions.

  4. Automobiles that are self-driving. A semi-autonomous vehicle may potentially use machine learning techniques to detect a partially visible object and alert the driver.

  5. Virtual assistants are a type of virtual helper. To analyze natural speech and provide information, smart assistants often blend supervised and unsupervised machine learning models. Behind the scenes, the engine is striving to reinforce recognised trends in the member’s online behaviour. If the member’s reading habits change and he or she fails to read postings from that group in the coming weeks, the news feed will be changed.