PhD in Machine learning (Transfer learning)
• Big Data: Hadoop , Map Reduce , Spark, Hive
• Programming language : Python, R,C++
• Machine learning:
Linear regression: Lasso, Ridge regression, Kernel regression.
Classification: Linear Classifier, SVM, Decision tree, Random forests, K-nearest neighbor, Naives Bayes Classifier,
Cluster & retrieval: Nearest neighbor, LDA, Gaussian mixture
Recommender system: Collaborative filtering, Matrix factorization
Dimensionality reduction: PCA
Algorithms: Gradient descent, stochastic gradient descent, boosting, KD-trees, K-mean, EM, ID3, Coordinate descent, Eigen decomposition, SVD
• Deep learning algorithm : CNN, RNN , LSTM,GAN ,
• ML Tool: Scikit-learn ,Tensorflow
• Operating system: Windows, linux