Machine Learning

 Machine Learning Programs 👉 Data Preprocessing in Machine Learning 👉 Data Preprocessing in Machine learning (Handling Missing values ) 👉 Linear Regression - ML Program - Weight Prediction 👉 Naïve Bayes Classifier - ML Program 👉 LOGISTIC REGRESSION - PROGRAM 👉 KNN Machine Learning Program 👉 Support Vector Machine (SVM) - ML Program 👉 Decision Tree Classifier on Iris Dataset 👉 Classification of Iris flowers using Random Forest 👉 DBSCAN 👉 Implement and demonstrate the FIND-S algorithm for finding the most specific hypothesis based on a given set of training data samples. Read the training data from a .CSV file 👉 For a given set of training data examples stored in a .CSV file, implement and demonstrate the Candidate-Elimination algorithm to output a description of the set of all hypotheses consistent with the training examples. 👉 Write a program to demonstrate the working of the decision tree based ID3 algorithm. Use an appropriate data set for building the decision tree and

  Machine Learning MCQs 👉1.  Machine Learning MCQs - UNIT 1 👉2.  Machine Learning MCQs-2 (Performance Metrics, Linear Regression, Naïve Bayes Classifier ) 👉3.  Machine Learning MCQs-3 (Logistic Regression, KNN, SVM, Decision Tree) 👉4.  Machine Learning MCQs - 4 (Clustering, Dimensionality Reduction) 👉5. Machine Learning MCQs - 5 (Ensemble Models)

                                                                                Git & GitHub Setup for MLOps Q1. Conflict in GIT When does a conflict arise in git? Choose the correct answer from below: A.     Always when 2 developers raise pull requests simultaneously. B.     Always when 2 developers change the project simultaneously. C.     When the same line of code of a particular file is changed, in 2 different merging branches A and B. D.     When the same file is deleted in 2 branches A and B, and we are trying to merge them. Ans: D Correct Option : When the same line of code of a particular file is changed, in 2 different merging branches A and B. Explanation : Conflicts generally arise when two people have changed the same lines in a file, or if one developer deleted a file while another developer was modifying it. In these cases, Git cannot automatically determine what is correct. Conflicts only affect the developer conducting the merg

  UNIT III RNN ------------------------------------------------------------------------------------------------------------------------ 1.      Handling Branches 2.      Layers 3.      Nodes 4.      Essential Elements 5.      Vanilla RNNs 6.      GRUs 7.      LSTM   👉  Deep Learning: UNIT 3 (A): RNN: Notes 👉 Deep Learning: UNIT 3 (A) : RNN : PPTs 👉  Deep Learning: UNIT- 3: RNN: Long Answer Questions 👉  Deep Learning: UNIT 3 : RNN : Short Answer Questions

                                                                               UNIT 3 RNN Short Answer Questions 1.      List the different types of Recurrent Neural Networks. 2.      List the different variants in of RNNs with RNN Nodes. 3.      What is the purpose of RNN? 4.      List the different applications of RNNs. 5.      Define RNN Layer. 6.      Define RNN Node. 7.      List the essential elements of RNN. 8.      How can you handle branches in RNN?

                                                                                                 UNIT 3 RNN Long Answer Questions 1.      Explain RNNLayer with neat diagram. 2.      Explain RNNNode with example. 3.      What is the drawback of Artificial Neural Network? How can you overcome that? Explain. 4.      Explain how RNNs handle sequential data. 5.      Explain the basic three structures of RNN 6.      What is the role of the hidden state in an RNN? 7.      What is a Recurrent Neural Network (RNN) and how does it differ from a feedforward neural network? 8.      Draw and explain the architecture of Recurrent Neural Networks. 9.      Draw and explain Schematic diagram of a recurrent neural network? 10.   List the different types of Recurrent Neural Networks. Explain them with example. 11.   Explain the essential elements of RNNNodes.  

  UNIT III (A) RNN -------------------------------------------------------------------------------------------------------------------- 1.      Handling Branches 2.      Layers 3.      Nodes 4.      Essential Elements