Blueocean Learning is a Bangalore based IT consulting, solutions and services organization of the last two decades with the bandwidth to train corporate bodies and individuals alike in all specialized technologies. We train organizations of all sizes, from small and medium-sized companies to global corporations.
Data science:
The need to store it has also grown as the world enters the era of big data. The main focus of the organizations has been on building a data warehousing framework and solutions. When frameworks such as Hadoop solve the storage problem, processing this data becomes a challenge, and data science begins to play a vital role in solving this problem. Data science is the future of AI because it can add value to your business.
With the aim of discovering hidden patterns from raw data, Data Science has a mixture of different tools, algorithms, and machine learning principles. This data science course explains how to process the history of data. Data science analyzes using advanced machine learning algorithms to determine the occurrence of a particular event. Data science looks at data from many angles sometimes from previously unknown angles. Data science is used to make decisions and make predictions using predictive causal analytics, descriptive analytics, and machine learning.
• Predictive Causal Analytics – This model is used to predict the probabilities of a particular event occurring in the future, for example, if you are giving money on credit, the issue of customers making future credit payments on time is a concern for you. We can build a model to predict whether or not future payments will be made on time using customer history.
• Prescriptive analytics: This model has the intelligence and the ability to make its own decisions using dynamic parameters.
We can run algorithms on data to bring intelligence to it. With a prescriptive analytics model, you can empower your car to make decisions like when to turn, which lane to take, and when to slow down or speed up.
• Machine Learning to Make Predictions – You can build a model to determine the future direction of a finance company using transactions under a supervised learning model. The fraud detection model can be trained using a history of fraudulent purchases by training your hardware.
• Machine Learning for Pattern Detection – This is the unsupervised model where you don’t have any predefined labels for grouping. The most popular style is assembly. To create a network by placing towers in an area, we can use clustering technology to find tower locations that will ensure that all users get optimal signal strength.
