Estimation Model IT Powerpoint Presentation Slides V

Slide 1: This slide displays the title Estimation Model (IT).
Slide 2: This slide displays the title Agenda for estimation model.
Slide 3: This slide exhibit table of content.
Slide 4: This slide showcase table of content that is to be discuss further.
Slide 5: This slide showcase table of content that is to be discuss further.
Slide 6: This slide represents the predictive analytics introduction that is used for forecasts action, behaviors, and trends using recent and past information.
Slide 7: This slide outlines the overview of the predictive analytics framework and its components, including wide area network, OpenFlow, forecasting, software-defined.
Slide 8: This slide depicts the overview of predictive analytics models, including the predictive problems they solve.
Slide 9: This slide showcase table of content that is to be discuss further.
Slide 10: This slide depicts the importance of predictive analytics in different industries.
Slide 11: This slide depicts the importance of predictive analytics that covers detecting fraud, improving operations, optimizing marketing campaigns, and reducing risks.
Slide 12: This slide showcase table of content that is to be discuss further.
Slide 13: This slide depicts the tools used for predictive analytics to perform operations in predictive models.
Slide 14: This slide represents the predictive analytics workflow that is widely used in managing energy loads in electric grids.
Slide 15: This slide represents the steps for predictive analytics workflow application in industries.
Slide 16: This slide showcase table of content that is to be discuss further.
Slide 17: This slide represents the difference between the main types of advanced analytics, and it includes diagnostic, descriptive, predictive, and prescriptive analytics.
Slide 18: This slide showcase table of content that is to be discuss further.
Slide 19: This slide describes the overview of the classification model used in predictive analytics, including the questions it answers.
Slide 20: This slide depicts the decision tree model of predictive analytics that are beneficial for quick decision-making and consists of decision node and leaf nodes.
Slide 21: This slide represents the random forest technique to implement a classification model that simultaneously works on individual subsets of sample data.
Slide 22: This slide showcase table of content that is to be discuss further.
Slide 23: This slide represents the overview of the clustering model of predictive analytics covering its two methods such as hard clustering and soft clustering.
Slide 24: This slide outlines the two primary information clustering methods used in the predictive analytics clustering model.
Slide 25: This slide showcase table of content that is to be discuss further.
Slide 26: This slide represents the regression model of predictive analytics that is most commonly used in statistical analysis.
Slide 27: This slide represents the types of the regression model, including its overview, examples, and usage percentage.
Slide 28: This slide showcase table of content that is to be discuss further.
Slide 29: This slide depicts the neural networks model of predictive analytics that behave in the same manner as a human brain does.
Slide 30: This slide depicts the different types of the neural network model, including their overview, use cases and usage.
Slide 31: This slide showcase table of content that is to be discuss further.
Slide 32: This slide outlines the introduction of the forecast model used for predictive analytics to make the metric value predictions for business processes.
Slide 33: This slide talks about the outliers model used for predictive analytics, including its use cases, impact and algorithm used in it.
Slide 34: This slide talks about the time series model of predictive analytics that makes future outcome predictions by taking time as input.
Slide 35: This slide showcase table of content that is to be discuss further.
Slide 36: This slide discusses the steps required to create predictive algorithm models for business processes.
Slide 37: This slide depicts the lifecycle of the predictive analytics model, and it includes highlighting & formulating a problem, data preparation, information exploration.
Slide 38: This slide depicts the working of predictive analytics models that operates iteratively.
Slide 39: This slide represents the development process of predictive analytics that uses recent and past information to predict behavior, actions, and trends.
Slide 40: This slide showcase table of content that is to be discuss further.
Slide 41: This slide outlines the application of predictive analytics in the healthcare department for forecasting the probability of patients having medical disorders.
Slide 42: This slide represents the application of predictive analytics in the finance and banking sector as they deal with vast amounts of data.
Slide 43: This slide talks about using predictive analytics in manufacturing forecasting for optimal use of resources.
Slide 44: This slide depicts the usage of predictive analytics technology in the government sector to improve cybersecurity.
Slide 45: This slide represents the application of predictive analytics technology in the retail industry in customer behavior analysis, improved customer service.
Slide 46: This slide outlines the use of predictive analytics in the marketing industry, where active traders develop a new campaign based on customer behavior.
Slide 47: This slide showcase table of content that is to be discuss further.
Slide 48: This slide represents the training program for the predictive analytics model, and it includes the name of teams, trainer names, modules to be covered in training.
Slide 49: This slide describes the budget for developing predictive analytics model by covering details of project cost summary, amount, project details.
Slide 50: This slide showcase table of content that is to be discuss further.
Slide 51: This slide talks about the checklist for predictive analytics deployment that is necessary for organizations before deploying it and avoiding possible mistakes.
Slide 52: This slide showcase table of content that is to be discuss further.
Slide 53: This slide depicts the roadmap for predictive analytics model development, including describing the project, information collection, information analysis.
Slide 54: This slide showcase table of content that is to be discuss further.
Slide 55: This slide represents the roadmap for predictive analytics model development, including the steps to be performed in the process.
Slide 56: This slide showcase table of content that is to be discuss further.
Slide 57: This slide represents the predictive analytics model performance tracking dashboard.
Slide 58: This is the icons slide.
Slide 59: This slide presents title for additional slides.
Slide 60: This slide describes the usage of predictive analytics in banking and other financial institutions for credit purposes.
Slide 61: This slide represents the application of predictive analytics in underwriting by insurance companies.
Slide 62: This slide represents the application of predictive analytics in fraud detection in various industries.
Slide 63: This slide represents the predictive analytics application in predictive maintenance and monitoring to avoid difficulties later.
Slide 64: This slide represents the comparison between predictive analytics and machine learning based on technology used.
Slide 65: This slide represents how predictive analytics can help the marketing industry find better customer leads.
Slide 66: This slide depicts how predictive analytics help identifies prospects faster in the marketing industry.
Slide 67: This slide describes how predictive analytics can help align sales and marketing better.
Slide 68: This slide outlines how predictive analytics can help understand existing customers' needs as many businesses depend on client retention and upsells.
Slide 69: This slide talks about marketing automation by predictive analytics, and this will reshape the market industry.
Slide 70: This slide outlines the use of predictive analytics for better budget allocation in the marketing industry.
Slide 71: This slide exhibits yearly profits stacked line charts for different products.
Slide 72: This slide depicts posts for past experiences of clients.
Slide 73: This slide shows puzzle for displaying elements of company.
Slide 74: This slide showcases financials of company.
Slide 75: This slide exhibits ideas generated.
Slide 76: This slide shows about your company, target audience and its client's values.
Slide 77: This slide display Venn diagram.
Slide 78: This slide shows about your company, target audience and its client's values.