Overview of Splunk Analytics for Hadoop Why Splunk Analytics for Hadoop What's splunk analytics Quick in Deploying as Well as in Extracting Data The Drag and Drop System Prosperous for Developers Communicative Research Output Can be Previewed Without Stopping the Process Splunk Analytics for Hadoop Advantages and...

Revolutionizing Enterprise Agility with HaaS What's make your agile with Hadoop-as-a-Service (HaaS) How does HaaS provide the above-stated benefits? Hadoop as a service Advantages Hadoop as a provider Disadvantages Applications of hadoop as a service Future jobs associated with Hadoop-as-a-Service (HaaS) Conclusion ...

What is Erwin Data Modeler? Key Features and Benefits Logical vs Physical Data Models Import/Export Features Normalization in Erwin Model Validation and Reporting Collaboration and Version Control Forward and Reverse Engineering in Erwin Best Practices for Data Modeling in Erwin Conclusion What is Erwin Data Modeler? Erwin...

What is Reinforcement Learning? Basics of Q Learning Q-Table and Q-Values Exploration vs Exploitation Q Learning Algorithm Environment and Rewards Applications (e.g., Game AI) Summary What is Reinforcement Learning ? Reinforcement Learning in Machine Learning Training where an agent learns to make decisions by performing actions in an...

Introduction to Regularization Understanding Overfitting Ridge vs Linear Regression Cost Function of Ridge Role of Lambda (Regularization Strength) Mathematical Formulation Implementation in Python Use Cases Summary Introduction to Regularization In machine learning, the goal is to build models that generalize well on unseen data....

Introduction to Bayes Theorem Mathematical Explanation Conditional Probability Naive Bayes Classifier Assumptions and Limitations Bayesian Networks Spam Detection with Bayes Parameter Estimation Conclusion Introduction to Bayes Theorem Bayes Theorem in Machine Learning is a fundamental concept in probability theory and statistics that...

Overview of TensorFlow Image Classification Project Object Detection Handwritten Digit Recognition Sentiment Analysis with TensorFlow Text Classification Time Series Forecasting TensorFlow with Keras Summary Overview of TensorFlow TensorFlow is an open-source Machine Learning Training framework developed by Google Brain. It’s...

Introduction to Bias and Variance High Bias vs High Variance Underfitting and Overfitting Bias-Variance Decomposition Impact on Model Accuracy Visualization of the Tradeoff Regularization to Control Variance Cross-validation Techniques Conclusion Introduction to Bias and Variance In the field of machine learning, understanding the...

Introduction to HMM Components of HMM Markov Chains vs HMM Transition and Emission Probabilities Forward and Backward Algorithms Viterbi Algorithm Baum-Welch Training Algorithm Applications in NLP and Bioinformatics Conclusion Introduction to Hidden Markov Models (HMM) Hidden Markov Models (HMMs) are powerful statistical tools used for...

Introduction to Game Theory The Classic Prisoner's Dilemma Payoff Matrix Explained Nash Equilibrium in the Dilemma Dominant Strategy Iterated Prisoner’s Dilemma Tit-for-Tat Strategy Real-World Applications (Economics, Politics) Conclusion Introduction to Game Theory Game theory is a branch of mathematics and economics that studies...