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Data Analysis

Data Analysis is the process of systematically applying statistical and/or logical techniques to describe and illustrate, condense and recap, and evaluate data.  An essential component of ensuring data integrity is the accurate and appropriate analysis of research findings. Machine learning is a method of data analysis that automates analytical model building. It is a branch of artificial intelligence based on the idea that systems can learn from data, identify patterns and make decisions with minimal human intervention. Importance.

Benefits of Data Analysis

  • Personalize the customer experience.
  • Inform business decision-making.
  • Streamline operations.
  • Mitigate risk and handle setbacks.
  • Enhance security.

Data visualization

Data visualization is the representation of data or information in a graph, chart, or other visual format.  Machine learning makes it easier to conduct analyses such as predictive analysis, which can then serve as helpful visualizations to present.

Advantages of Data visualization

  • Better analysis.
  • Quick action.
  • Identifying patterns.
  • Finding errors.
  • Understanding the story.
  • Exploring business insights.
  • Grasping the Latest Trends

Logistic regression

Logistic regression is a supervised learning classification algorithm used to predict the probability of a target variable. The nature of target or dependent variable is dichotomous, which means there would be only two possible classes.

Logistic regression Benefits

  • Logistic regression is easier to implement, interpret, and very efficient to train.
  • It makes no assumptions about distributions of classes in feature space.
  • It can easily extend to multiple classes(multinomial regression) and a natural probabilistic view of class predictions.
  • It not only provides a measure of how appropriate a predictor(coefficient size)is, but also its direction of association (positive or negative).

Natural Language Processing

NLP is a field in machine learning with the ability of a computer to understand, analyze, manipulate, and potentially generate human language. NLP in Real Life. Information Retrieval(Google finds relevant and similar results).

Benefits of Natural Language Processing

  • Enable Natural Conversations. Chatbots have a hard time making sense of human language, which is full of complex patterns, structural conventions, and strange idioms.
  • Allocate Human Resources Effectively.
  • Reduce Costs and Inefficiencies. 
  • Improve Customer Satisfaction. 
  • Benefit from Market Research and Analysis.

Neural Network

An artificial neural network is an attempt to simulate the network of neurons that make up a human brain so that the computer will be able to learn things and make decisions in a humanlike manner. ANNs are created by programming regular computers to behave as though they are interconnected brain cells.

Advantages of Neural Network

  • Neural Networks have the ability to learn by themselves and produce the output that is not limited to the input provided to them.
  • The input is stored in its own networks instead of a database, hence the loss of data does not affect its working.
  • These networks can learn from examples and apply them when a similar event arises, making them able to work through real-time events.
  • Even if a neuron is not responding or a piece of information is missing, the network can detect the fault and still produce the output.
  • They can perform multiple tasks in parallel without affecting the system performance.

Deep learning 

Deep learning is an artificial intelligence (AI) function that imitates the workings of the human brain in processing data and creating patterns for use in decision making. … Also known as deep neural learning or deep neural network.

Benefits of Deep learning 

  • No Need for Feature Engineering.
  • Best Results with Unstructured Data. 
  • No Need for Labeling of Data. 
  • Efficient at Delivering High-quality Results. 
  • The Need for Lots of Data. 
  • Neural Networks at the Core of Deep Learning are Black Boxes.

Big data

Big data analytics can make sense of the data by uncovering trends and patterns. Machine learning can accelerate this process with the help of decision-making algorithms.

Benefits of Big data 

  • Using big data cuts your costs. 
  • Using big data increases your efficiency. 
  • Using big data improves your pricing. 
  • You can compete with big businesses.
  • Allows you to focus on local preferences. 
  • Using big data helps you increase sales and loyalty.
  • Using big data ensures you hire the right employees.
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