Category: Analytics and Machine Learning Project Development

Data Analytics Project: Problem Framing and Project Lifecycle

REF: Internet and Gregory S. Nelson. The Analytics Lifecycle Toolkit: A Practical Guide fo an Effective  Analytics Capability,  John Wiley & Sons © 2018 . Chapter 6 – Problem Framing Data Analytics, Machine Learning Data Analytics, Machine Learning, Data Science

Model Selection

• Optimizations/Machine Learning/Data Mining/Deep Learning/Reinforcement Learning/Graph Mining/NLP/Genetic Algorithms • Regression • Linear • Non-Linear • Classifications • Logistics Regression • Sigmoid : Binary • Softmax: Multi-Class • Bayes Classifier • SVM • Bayesian: Regression/Classification • Clustering • K-NN • KNN+ • Kmeans, Hierarchical, Density •Machine Learning/Data Mining/Deep Learning/Reinforcement Learning/Graph Mining/NLP •Time Series Analysis •Decision (Regression, …

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Model Selection for your Project

Potential Models • Statistical Models • Parametric and Non-Parametric • Mathematical Model (Optimization) • Machine Learning • Data Mining • Deep Learning • Reinforcement Learning • Graph Mining • NLP • Optimization • Genetic Algorithm •Association •Basket Association •Apriori Algorithm •Supervised •Classification •Regression •Unsupervised •Clustering/Customer Segmentation •Reinforcement •Learn a policy (interactively) •Game Playing •Robot in …

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Possible Data Analytics Project Goals

• Examine relations • Test Hypothesis • Validate • Find groups/classes/rules • Learn a policy • Maximize Reward interactively • Predict (Class or Value) • Forecast (numeric, sales) • Compare • Classify • Cluster Data Analytics, Machine Learning, Data Science

Experimental Design Examples (Data Analytics Projects)

Data Analytics, Machine Learning, Data Science

Evaluating Your Data Analytics Project Outcome

Regression Projects • R Square, Goodness of fit • RMSE Classification Projects • Confusion Matrix • ROC • Accuracy, Recall, Precision RL – Reinforcement • Reward – Cumulative Data Analytics, Machine Learning, Data Science

Dimensionality Reduction

Some Approaches •Feature Selection •Feature Extraction •PCA •SVD •LDA Data Analytics, Machine Learning, Data Science

Initial Analysis of Text and Image Data (Data Analytics and ML Projects)

Initial Analysis of Text Data • Stop word filter • Lemma • POS • Vocabulary Analysis Image Data: Initial Analysis • Fix image size, ratios • Image Scaling • Transform to Gray • Standardize Data Analytics, Machine Learning, Data Science

Data Requirements for Data Analytics Projects

Data • Dataset Characteristics •Large Scale, Real, Representative, Relevant Features, balanced classes, unit relevant • Adapting data/dataset for the project •Clean, normalize/standardize, bring more data, and bring more data of the missing type • Data Suitability for the project • Check for R Square Measure • Check for Bias, Variance, • Do Exploratory Analysis • …

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Initial and Exploratory Analysis for Data Analytics Projects

To have a thorough understanding of the data. Two Types: • Initial Analysis • Exploratory Analysis Initial Analysis: Univariate Analysis • Deciding/Determining the dependent (target) variable • Assigning the correct data types, appropriate column names • Address: Inconsistencies, missing values, outliers • Categorical variables with too many levels (address the issue) • (understand) Distributions of …

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