<a href="https://www.mytectra.com/interview-question/human-resourse-hr-interview-questions/">Human Resource (HR) Interview Questions</a> <a href="https://www.mytectra.com/interview-question/selenium-interview-questions-and-answers/">Selenium Interview Questions and Answers</a> <a href="https://www.mytectra.com/interview-question/javascript-interview-questions/">Javascript Interview Questions</a>
Mastering Machine Learning
myTectra offers Machine Learning Training in Bangalore using Class Room. myTectra offers Live Online Machine Learning Training Globally.
Installation and configuration
Data Preprocessing
Regression Techniques
Simple Linear Regression
Multiple Linear Regression
Polynomial Linear Regression
Support Vector Regression
Decision Tree Regression
Random Forest Regression
Evaluating Regression Model Performance
Classification Techniques
K-Nearest Neighbors (KNN)
Support Vector Machine (SVM)
Kernel SVM
Naïve Bayes Classification
Decision Tree Classification
Random Forest Classification
Evaluating Classification Model Performance
Natural Language Processing (NLP)
Basic of NLP
Language preprocessing Techniques
Auto summarizing the given text document
Clustering Techniques
K-Means Clustering
K-mini Batch Clustering
Hierarchical Clustering
Elbow Method
Curve Smoothening Techniques
Association Rule Learning
Reinforcement Learning
Basics of Numpy and panda
Deep Learning
Basics/what is Deep Learning
Artificial Neural Networks
Dimension Reduction Techniques
Principal Component Analysis (PCA)
Linear Discriminant Analysis (LDA)
Statistics Basics
Standard Deviation
Variance
Co-Variance
T-distribution
Pearson Correlation Coefficient (PCC)/ Correlation Coefficient
Data Preprocessing
Regression Techniques
Simple Linear Regression
Multiple Linear Regression
Polynomial Linear Regression
Support Vector Regression
Decision Tree Regression
Random Forest Regression
Evaluating Regression Model Performance
Classification Techniques
K-Nearest Neighbors (KNN)
Support Vector Machine (SVM)
Kernel SVM
Naïve Bayes Classification
Decision Tree Classification
Random Forest Classification
Evaluating Classification Model Performance
Natural Language Processing (NLP)
Basic of NLP
Language preprocessing Techniques
Auto summarizing the given text document
Clustering Techniques
K-Means Clustering
K-mini Batch Clustering
Hierarchical Clustering
Elbow Method
Curve Smoothening Techniques
Association Rule Learning
Reinforcement Learning
Basics of Numpy and panda
Deep Learning
Basics/what is Deep Learning
Artificial Neural Networks
Dimension Reduction Techniques
Principal Component Analysis (PCA)
Linear Discriminant Analysis (LDA)
Statistics Basics
Standard Deviation
Variance
Co-Variance
T-distribution
Pearson Correlation Coefficient (PCC)/ Correlation Coefficient
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Top 25 Python Interview Questions Prepared by Experts
1. What is JSON? How would convert JSON data into Python data? JSON – stands for JavaScript Object Notation. It is a popular data format for storing data in NoSQL databases. Generally JSON is built on 2 structures. A collection of <name, value> pairs. An ordered list of values. As Python supports JSON parsers, JSON-based data is actually represented as a dictionary in Python. You can convert json data into python using load() of json module. 2. How are the functions help() and dir() different? These are the two functions that are accessible from the Python Interpreter. These two functions are used for viewing a consolidated dump of built-in functions. help() – it will display the documentation string. It is used to see the help related to modules, keywords, attributes, etc. To view the help related to string datatype, just execute a statement help(str) – it will display the documentation for ‘str, module. ◦ Eg: ...
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