Data Science course in Malaysia
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What’s Data Science and its use in machine learning and analytics
Data Science is a term that is very common, so what does it exactly mean? What is the dissimilarity between Data Science and BI? What skills would you need for Data Scientist? How are predictions and decisions made in Data Science? So, these are some important questions that are going to be answered here. know more about data science course
First, let us understand what exactly is Big Data Science? It is a mixture of different algorithms, tools, and machine learning values with the only goal to discover the hidden patterns from raw data. So, how is it different from statisticians doing it for years? The answer is the major difference between predicting and explaining.
Data Science v/s Data Analyst
Data Analyst generally explains what’s going on just by processing the history of data. Data Scientist just only does an exploratory analysis for discovering the insights from it, however, uses different advanced learning algorithms that will identify the happening of any particular event in the future. Data Scientist looks at this data from different angles, and sometimes angles are not known before. Thus, Data Science is mainly used to make predictions and decisions by using prescriptive analytics, machine learning, and predictive causal analytics.
Prescriptive analytics: Suppose you want the model that has the intelligence of taking your own decisions and capability to modify with the dynamic parameters, certainly you need the prescriptive analytics for the task. This new field is about giving the right advice. So, it not just predicts but suggests different prescribed actions and outcomes.
Machine learning to make predictions —suppose you have the transaction data of the finance firm and want to build the model that will determine its future trend, machine learning algorithms will be the right bet. It falls under a paradigm of supervised learning. This is called supervised as you have data based on that you can guide your machines. For example, the fraud-detection model is trained using the historical record of fraudulent purchases.
Predictive causal analytics – Suppose you want the model that will predict possibilities of an event in the future, you have to apply for predictive causal analytics. And, suppose you are giving money on credit, the probability of the customers making any future payments timely is a matter of concern to you. Here, you will be able to build the model that will perform the predictive analytics on the payment history of your customer to know if future payments are timely or not.
Machine learning for the pattern discovery —suppose you do not have the right parameters where you can make any predictions, you have to find out hidden patterns in a dataset to make meaningful predictions. It is an unsupervised model since you do not have predefined levels of grouping. The most common algorithm that is used for the pattern discovery is the Clustering.
Suppose you’re working in the telephone firm and you want to establish the network by putting certain towers in the area. You can use clustering methods to find such tower locations that can ensure all users get optimum signal strength.
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There are some leading big data training companies that provide professional Hadoop courses in Pune. The students can ensure that they will get the best big data course content from the industry. Participants who are looking to build their career may opt for data training certification from here.
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