Software classification (Hard Level) Test

670922 Ratings

Topics covered - Syllabus

  • advantages and limitations
  • algorithms- svm
  • algorithms- tuning
  • alpha-beta pruning
  • Analytics
  • applications- text mining
  • artificial NN- neural network
  • assumption- Manifold assumption
  • Bayesian network
  • binomial distribution
  • Boosted trees
  • Breadth first search
  • classification- supervised learning, unsupervised learning
  • Clustering
  • component analysis
  • convolutional NN- neural network
  • Cross Validation
  • data pipeline
  • data separation
  • decision trees
  • Deep Learning
  • deep neural networks
  • deep nn
  • Depth first search
  • dev error
  • distance metrics
  • face recognition
  • factor model
  • fault tolerance
  • fault tolerant system
  • forest method
  • future
  • GPGPU and CUDA
  • Interpolation
  • k-mean clustering
  • Logistic regression
  • markov model
  • neural network- fully connected
  • neural network- partially connected
  • NLP
  • NOSQL
  • opencv, computer vision
  • Outlier treatment
  • Overview
  • Pattern Recognition
  • Perceptron
  • probabilistic graphical model
  • Probability distribution
  • Python- data science
  • R- feature exploration
  • recommender system
  • recurrent NN- neural network
  • Regression
  • Reinforcement learning
  • semi supervised learning
  • softwares
  • statistical analysis- model
  • statistical language model
  • supervised learning
  • test error
  • training data
  • training error
  • transduction
  • transfer learning
  • Types

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Total Passed - 47257

Total Failed - 882661

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