Dr. Jamal Amani Rad currently works in Choice Modelling Centre and Institute for Transport Studies, University of Leeds, Leeds LS2 9JT, UK He obtained his PhD in Mathematics at the Department of Mathematics at University of Shahid Beheshti. His research interests include modelling, numerics, and analysis of partial differential equations by using meshless methods, with an emphasis on applications from finance. Dr. Snehashish Chakraverty is a Senior Professor in the Department of Mathematics (Applied Mathematics Group), National Institute of Technology Rourkela, with over 30 years of teaching and research experience. A gold medalist from the University of Roorkee (now IIT Roorkee), he earned his Ph.D. from IIT Roorkee and completed post-doctoral work at the University of Southampton (UK) and Concordia University (Canada). He has also served as a visiting professor in Canada and South Africa. Dr. Chakraverty has authored/edited 38 books and published over 495 research papers. His research spans differential equations (ordinary, partial, fractional), numerical and computational methods, structural and fluid dynamics, uncertainty modeling, and soft computing techniques. He has guided 27 Ph.D. scholars, with 10 currently under his supervision.He has led 16 funded research projects and hosted international researchers through prestigious fellowships. Recognized in the top 2% of scientists globally (Stanford-Elsevier list, 2020–2024), he has received numerous awards including the CSIR Young Scientist Award, BOYSCAST Fellowship, INSA Bilateral Exchange, and IOP Top Cited Paper Awards. He is Chief Editor of International Journal of Fuzzy Computation and Modelling and serves on several international editorial boards.Dr. Kourosh Parand is a Professor in International Business University, Toronto, Canada . His main research field is Scientific Computing, Spectral Methods, Meshless methods, Ordinary Differential Equations (ODEs), Partial Differential Equations(PDEs) and Computational Neuroscience Modeling.

• Part 1: Introduction to Machine Learning and Data Life Cycle1. Basics of Machine Learning2. Essential Mathematics for Machine Learning3. Feature Selection MethodsPart 2: Linear Methods for Dimension Reduction4. Principal Component Analysis5. Linear Discriminant AnalysisPart 3: Non-Linear Methods for Dimension Reduction6. Linear Local Embedding7. Multi-dimensional Scaling8. t-distributed Stochastic Neighbor EmbeddingPart 4: Deep Learning Methods for Dimension Reduction9. Feature Extraction and Deep Learning10. Autoencoders11. Dimensionality reduction in deep learning through group actions

Dr. Jamal Amani Rad currently works in Choice Modelling Centre and Institute for Transport Studies, University of Leeds, Leeds LS2 9JT, UK He obtained his PhD in Mathematics at the Department of Mathematics at University of Shahid Beheshti. His research interests include modelling, numerics, and analysis of partial differential equations by using meshless methods, with an emphasis on applications from finance. Dr. Snehashish Chakraverty is a Senior Professor in the Department of Mathematics (Applied Mathematics Group), National Institute of Technology Rourkela, with over 30 years of teaching and research experience. A gold medalist from the University of Roorkee (now IIT Roorkee), he earned his Ph.D. from IIT Roorkee and completed post-doctoral work at the University of Southampton (UK) and Concordia University (Canada). He has also served as a visiting professor in Canada and South Africa. Dr. Chakraverty has authored/edited 38 books and published over 495 research papers. His research spans differential equations (ordinary, partial, fractional), numerical and computational methods, structural and fluid dynamics, uncertainty modeling, and soft computing techniques. He has guided 27 Ph.D. scholars, with 10 currently under his supervision.He has led 16 funded research projects and hosted international researchers through prestigious fellowships. Recognized in the top 2% of scientists globally (Stanford-Elsevier list, 2020–2024), he has received numerous awards including the CSIR Young Scientist Award, BOYSCAST Fellowship, INSA Bilateral Exchange, and IOP Top Cited Paper Awards. He is Chief Editor of International Journal of Fuzzy Computation and Modelling and serves on several international editorial boards.Dr. Kourosh Parand is a Professor in International Business University, Toronto, Canada . His main research field is Scientific Computing, Spectral Methods, Meshless methods, Ordinary Differential Equations (ODEs), Partial Differential Equations(PDEs) and Computational Neuroscience Modeling.

• Part 1: Introduction to Machine Learning and Data Life Cycle1. Basics of Machine Learning2. Essential Mathematics for Machine Learning3. Feature Selection MethodsPart 2: Linear Methods for Dimension Reduction4. Principal Component Analysis5. Linear Discriminant AnalysisPart 3: Non-Linear Methods for Dimension Reduction6. Linear Local Embedding7. Multi-dimensional Scaling8. t-distributed Stochastic Neighbor EmbeddingPart 4: Deep Learning Methods for Dimension Reduction9. Feature Extraction and Deep Learning10. Autoencoders11. Dimensionality reduction in deep learning through group actions

Dr. Jamal Amani Rad currently works in Choice Modelling Centre and Institute for Transport Studies, University of Leeds, Leeds LS2 9JT, UK He obtained his PhD in Mathematics at the Department of Mathematics at University of Shahid Beheshti. His research interests include modelling, numerics, and analysis of partial differential equations by using meshless methods, with an emphasis on applications from finance. Dr. Snehashish Chakraverty is a Senior Professor in the Department of Mathematics (Applied Mathematics Group), National Institute of Technology Rourkela, with over 30 years of teaching and research experience. A gold medalist from the University of Roorkee (now IIT Roorkee), he earned his Ph.D. from IIT Roorkee and completed post-doctoral work at the University of Southampton (UK) and Concordia University (Canada). He has also served as a visiting professor in Canada and South Africa. Dr. Chakraverty has authored/edited 38 books and published over 495 research papers. His research spans differential equations (ordinary, partial, fractional), numerical and computational methods, structural and fluid dynamics, uncertainty modeling, and soft computing techniques. He has guided 27 Ph.D. scholars, with 10 currently under his supervision.He has led 16 funded research projects and hosted international researchers through prestigious fellowships. Recognized in the top 2% of scientists globally (Stanford-Elsevier list, 2020–2024), he has received numerous awards including the CSIR Young Scientist Award, BOYSCAST Fellowship, INSA Bilateral Exchange, and IOP Top Cited Paper Awards. He is Chief Editor of International Journal of Fuzzy Computation and Modelling and serves on several international editorial boards.Dr. Kourosh Parand is a Professor in International Business University, Toronto, Canada . His main research field is Scientific Computing, Spectral Methods, Meshless methods, Ordinary Differential Equations (ODEs), Partial Differential Equations(PDEs) and Computational Neuroscience Modeling.

• Part 1: Introduction to Machine Learning and Data Life Cycle1. Basics of Machine Learning2. Essential Mathematics for Machine Learning3. Feature Selection MethodsPart 2: Linear Methods for Dimension Reduction4. Principal Component Analysis5. Linear Discriminant AnalysisPart 3: Non-Linear Methods for Dimension Reduction6. Linear Local Embedding7. Multi-dimensional Scaling8. t-distributed Stochastic Neighbor EmbeddingPart 4: Deep Learning Methods for Dimension Reduction9. Feature Extraction and Deep Learning10. Autoencoders11. Dimensionality reduction in deep learning through group actions