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Data Science Projects
The following projects were created during my studies for M.Sc. at the Ben-Gurion University of the Negev.
They compose a part of my studies, additional projects can be found here or in my github.
Deep learning Course
Deep learning algorithms have recorded significant achievements in diverse areas such as image recognition, Text analysis, and robotics. ANN, CNN, RNN, and GAN projects.
Machine Learning Course
The course reviews different families of computational learning algorithms such as Neural Networks, Vector Machines, Decision Trees, Ensemble methods (Random Forest, AdaBoost...), SVM, Regression methods (Logistics Regression, Lasso)...
The Art of Analyzing Big Data
The course discusses principles, methodologies, and techniques for mining massive datasets. classification, clustering analysis, and recommendation using the principles of parallel and distributed processing.
Analysis of Sustainable Building
The final project created for the course "The Art of Analyzing Big Data - The Data Scientist Toolbox". The directive for this project was to gather, process, and analyze data on a chosen topic that is related to the housing market.
Disease Identification in Tomato Plants Images using Transfer Learning and InceptionV3
High performance CNN model for recognizing disease in tomato plants
Deep Reinforcement Learning Course
Tasks that were created as part of the Deep Reinforcement Learning (DRL) course. The course provided the theoretical and practical knowledge required to apply DRL techniques in their research.
Natural Language Processing Course
Tasks that were created as part of the Natural Language Processing (NLP) course. Automatically process large amounts of text in order to understand given texts and generate new texts.
Data Mining and Data Warehousing
Tasks that were created as part of the Data Mining and Data Warehousing course. The course covers Decision Trees, Info-Fuzzy Networks, Artificial Neural Networks, Bayesian Learning, Instance-Based Learning, Support Vector Machines, Association Rules, and Cluster Analysis.
Deep learning Course
Deep learning algorithms have recorded significant achievements in diverse areas such as image recognition, Text analysis, and robotics. ANN, CNN, RNN, and GAN projects.
Machine Learning Course
The course reviews different families of computational learning algorithms such as Neural Networks, Vector Machines, Decision Trees, Ensemble methods (Random Forest, AdaBoost...), SVM, Regression methods (Logistics Regression, Lasso)...
The Art of Analyzing Big Data
The course discusses principles, methodologies, and techniques for mining massive datasets. classification, clustering analysis, and recommendation using the principles of parallel and distributed processing.
Analysis of Sustainable Building
The final project created for the course "The Art of Analyzing Big Data - The Data Scientist Toolbox". The directive for this project was to gather, process, and analyze data on a chosen topic that is related to the housing market.
Disease Identification in Tomato Plants Images using Transfer Learning and InceptionV3
High performance CNN model for recognizing disease in tomato plants
Deep Reinforcement Learning Course
Tasks that were created as part of the Deep Reinforcement Learning (DRL) course. The course provided the theoretical and practical knowledge required to apply DRL techniques in their research.
Natural Language Processing Course
Tasks that were created as part of the Natural Language Processing (NLP) course. Automatically process large amounts of text in order to understand given texts and generate new texts.
Data Mining and Data Warehousing
Tasks that were created as part of the Data Mining and Data Warehousing course. The course covers Decision Trees, Info-Fuzzy Networks, Artificial Neural Networks, Bayesian Learning, Instance-Based Learning, Support Vector Machines, Association Rules, and Cluster Analysis.
Deep learning Course
Deep learning algorithms have recorded significant achievements in diverse areas such as image recognition, Text analysis, and robotics. ANN, CNN, RNN, and GAN projects.
Machine Learning Course
The course reviews different families of computational learning algorithms such as Neural Networks, Vector Machines, Decision Trees, Ensemble methods (Random Forest, AdaBoost...), SVM, Regression methods (Logistics Regression, Lasso)...
The Art of Analyzing Big Data
The course discusses principles, methodologies, and techniques for mining massive datasets. classification, clustering analysis, and recommendation using the principles of parallel and distributed processing.
Analysis of Sustainable Building
The final project created for the course "The Art of Analyzing Big Data - The Data Scientist Toolbox". The directive for this project was to gather, process, and analyze data on a chosen topic that is related to the housing market.
Disease Identification in Tomato Plants Images using Transfer Learning and InceptionV3
High performance CNN model for recognizing disease in tomato plants
Deep Reinforcement Learning Course
Tasks that were created as part of the Deep Reinforcement Learning (DRL) course. The course provided the theoretical and practical knowledge required to apply DRL techniques in their research.
Natural Language Processing Course
Tasks that were created as part of the Natural Language Processing (NLP) course. Automatically process large amounts of text in order to understand given texts and generate new texts.
Data Mining and Data Warehousing
Tasks that were created as part of the Data Mining and Data Warehousing course. The course covers Decision Trees, Info-Fuzzy Networks, Artificial Neural Networks, Bayesian Learning, Instance-Based Learning, Support Vector Machines, Association Rules, and Cluster Analysis.
Deep learning Course
Deep learning algorithms have recorded significant achievements in diverse areas such as image recognition, Text analysis, and robotics. ANN, CNN, RNN, and GAN projects.
Machine Learning Course
The course reviews different families of computational learning algorithms such as Neural Networks, Vector Machines, Decision Trees, Ensemble methods (Random Forest, AdaBoost...), SVM, Regression methods (Logistics Regression, Lasso)...
The Art of Analyzing Big Data
The course discusses principles, methodologies, and techniques for mining massive datasets. classification, clustering analysis, and recommendation using the principles of parallel and distributed processing.
Analysis of Sustainable Building
The final project created for the course "The Art of Analyzing Big Data - The Data Scientist Toolbox". The directive for this project was to gather, process, and analyze data on a chosen topic that is related to the housing market.
Disease Identification in Tomato Plants Images using Transfer Learning and InceptionV3
High performance CNN model for recognizing disease in tomato plants
Deep Reinforcement Learning Course
Tasks that were created as part of the Deep Reinforcement Learning (DRL) course. The course provided the theoretical and practical knowledge required to apply DRL techniques in their research.
Natural Language Processing Course
Tasks that were created as part of the Natural Language Processing (NLP) course. Automatically process large amounts of text in order to understand given texts and generate new texts.
Data Mining and Data Warehousing
Tasks that were created as part of the Data Mining and Data Warehousing course. The course covers Decision Trees, Info-Fuzzy Networks, Artificial Neural Networks, Bayesian Learning, Instance-Based Learning, Support Vector Machines, Association Rules, and Cluster Analysis.
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