Analytics data science & artificial intelligence pdf
Introduction;
analytics data science & artificial intelligence pdf
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What is Analytics?
Analytics is a discipline of business and the social sciences that seeks to interpret the past and predict future events, primarily through the use of data mining techniques. It is also a specialized field of study within computer science or information systems.
The term was coined in 1970 by Harvard professor Eugene Fama,
who called it the process of turning data into information. Analytics can be used for predicting future results and analyzing current situations.
Businesses have always had to make decisions about what products to offer for sale,
how much inventory to carry, which employees to hire, how much research and development to spend on new products, and what investments should be made with borrowed money;
But never before has there been such an avalanche of quantitative information available from so many different sources.
What is Data Science?
Data Science is the use of various tools and techniques, such as statistical models and machine learning algorithms, to extract knowledge from data. It overlaps with a variety of disciplines, including computer science, statistics, mathematics, and business analytics. Data Science also has important applications in healthcare and other areas.
The discipline is typically broken into two broad categories:
Exploratory Data Analysis (EDA), which includes unstructured forms of analysis; and Predictive Data Analysis (PDA),
which includes more traditional forms of structured analysis.
Predictive Data Analytics can be used to create new mathematical models that can accurately predict trends or behaviors based on historical records.
What is Artificial Intelligence?
Artificial Intelligence is the branch of computer science that deals with the theory and development of intelligent machines. AI research is concerned with the question of how to make machines that can act intelligently. The question has been a major area of AI research since Alan Turing’s paper Computing Machinery and Intelligence published in 1950, which proposed what is now called the Turing Test as a criterion of intelligence. A more modern definition might be a branch of computer science dealing with intelligent agents: anything from programs that solve problems to robots that have common sense.
How do these three fields intersect?
Data analytics is the process of gathering, analyzing, and reporting numerical information.
Data Science is the practice of extracting knowledge from these numbers to help solve problems in an organization.
Artificial Intelligence is a branch of computer science that explores how computers can be programmed to behave more as humans do.
Data analytics, as well as data sciences, are driven by AI techniques such as machine learning and deep learning. These fields all intersect with one another because they rely on each other for input into the process.
A company will typically start with collecting its data through some form of analytics software.
They will then use that data to make predictions or analyses about the company’s business performance or future behavior which requires the use of predictive analysis and data science.
Once those analyses have been completed,
It will usually require some form of automation using either machine learning or deep learning methods to take over the manual tasks
which would otherwise need to be done by humans, respectively.
In summary, these three fields all rely heavily on one another due to their close-knit nature for them to function properly.
The future of Analytics, Data Science, and Artificial Intelligence;
1) What is Data Science? Data Science is a cross-discipline that combines analytical skills from fields like computer science,
mathematics, and statistics with insights from social sciences like sociology or psychology.
It helps businesses innovatively understand their customers so that they can offer them personalized services and products.
2) What does Artificial Intelligence (AI) have to do with data? AI refers to the field of computer science that aims at designing computers capable of doing things as humans do such as learning, recognizing objects, and solving problems by trial and error.
In essence, AI lets machines think for themselves. The application of AI in the context of analytics enables better predictions based on existing datasets without any intervention from human beings.
3) What are some applications of AI in Data Science? Some examples include: using customer feedback for product improvement;
sentiment analysis for understanding consumer behavior; pattern detection for fraud detection; predictive modeling for predicting customer needs;
chatbots as virtual customer service agents; virtual assistants like Siri or Cortana; automated decision-making systems etc.
Conclusion;
Analytics is the process of collecting and analyzing data to gain insights into customer behavior and usage patterns.
Data Science is the process of extracting knowledge from raw information to make predictions or infer conclusions.
Artificial Intelligence refers to the development of computers that act like humans, displaying intelligent behavior.
The use of these three technologies will help businesses better track and understand customer behavior, which will increase revenue.
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