diff --git a/Data Science/Julia_for_data_science_Jose_Storopoli_2016.pdf b/Data Science/Julia_for_data_science_Jose_Storopoli_2016.pdf new file mode 100644 index 00000000..6b47d9f3 Binary files /dev/null and b/Data Science/Julia_for_data_science_Jose_Storopoli_2016.pdf differ diff --git a/Machine Learning/Understanding_Deep_Learning_By_Simon_JD_Prince_2025.pdf b/Machine Learning/Understanding_Deep_Learning_By_Simon_JD_Prince_2025.pdf new file mode 100644 index 00000000..1e72eb70 Binary files /dev/null and b/Machine Learning/Understanding_Deep_Learning_By_Simon_JD_Prince_2025.pdf differ diff --git a/src/data/books.ts b/src/data/books.ts index 7c933696..237498ba 100644 --- a/src/data/books.ts +++ b/src/data/books.ts @@ -399,126 +399,140 @@ export const books: Book[] = [ }, // Machine Learning - { - id: "ml-1", - title: "Hands-On Machine Learning", - author: "Aurélien Géron", - category: "Machine Learning", - language: "Python", - pages: 856, - year: 2022, - description: "Practical guide to ML with Scikit-Learn, Keras, and TensorFlow.", - downloadLink: "https://github.com/avinash201199/Free-programming-books/tree/main/Machine%20Learning", - level: "Intermediate", - tags: ["Machine Learning", "Python", "TensorFlow", "Scikit-Learn"], - featured: true -}, -{ - id: "ml-2", - title: "Pattern Recognition and Machine Learning", - author: "Christopher Bishop", - category: "Machine Learning", - language: "General", - pages: 738, - year: 2006, - description: "Comprehensive introduction to the fields of pattern recognition and machine learning.", - downloadLink: "https://github.com/avinash201199/Free-programming-books/tree/main/Machine%20Learning", - level: "Advanced", - tags: ["Machine Learning", "Pattern Recognition", "Theory"] -}, -{ - id: "ml-3", - title: "Deep Learning", - author: "Ian Goodfellow, Yoshua Bengio, Aaron Courville", - category: "Machine Learning", - language: "General", - pages: 801, - year: 2016, - description: "Deep Learning is one of the most widely recognized and authoritative books covering modern deep learning theory, algorithms, and applications.", - downloadLink: "https://github.com/avinash201199/Free-programming-books/tree/main/Machine%20Learning", - level: "Advanced", - tags: ["Deep Learning", "Neural Networks", "AI"] -}, -{ - id: "ml-4", - title: "Machine Learning", - author: "Saikat Dutt, Subramanian Chandramouli, Amit Kumar Das", - category: "Machine Learning", - language: "General", - pages: 741, - year: 2016, - description: "The Beginner textbook on Machine Learning from Pearson.", - downloadLink: "https://github.com/avinash201199/Free-programming-books/tree/main/Machine%20Learning", - level: "Beginner", - tags: ["Machine Learning", "ML", "DS"] -}, -{ - id: "ml-5", - title: "Mathematics for Machine Learning", - author: "Marc Peter Deisenroth, A. Aldo Faisal, Cheng Soon Ong", - category: "Machine Learning", - language: "General", - pages: 417, - year: 2020, - level: "All Levels", - description: "the foundational tools and concepts of mathematics needed to understand and develop machine learning algorithms", - downloadLink: "https://github.com/avinash201199/Free-programming-books/blob/main/Machine%20Learning/mathematics%20for%20ml.pdf", - tags: ["MachineLearning", "Mathematics", "Optimization", "MLAlgorithms"], - featured: true -}, -{ - id: "ml-6", - title: "The Little Book of Deep Learning", - author: "François Fleuret", - category: "Machine Learning", - language: "General", - pages: 129, - year: 2023, - level: "Intermediate", - description: "A concise and practical introduction to deep learning, covering fundamental concepts, architectures, and techniques in a clear and accessible manner for practitioners and students.", - downloadLink: "https://fleuret.org/public/lbdl.pdf", - tags: ["DeepLearning", "NeuralNetworks", "MachineLearning", "AI", "Practical"], - featured: true -}, -{ - id: "ml-7", - title: "Neural Networks", - author: "Simon Haykin", - category: "Machine Learning", - language: "General", - pages: 823, - year: 2005, - description: "Neural Networks: A Comprehensive Foundation is a complete guide to understanding, designing, and applying neural networks in theory and practice.", - downloadLink: "https://github.com/avinash201199/Free-programming-books/tree/main/Machine%20Learning", - level: "Advanced", - tags: ["Deep Learning", "Neural Networks", "AI"] -}, -{ - id: "ml-8", - title: "Neural Network Design", - author: "Martin T. Hagan", - category: "Machine Learning", - language: "General", - pages: 1012, - year: 1995, - description: "Neural Network Design by Martin T. Hagan is a practical guide to designing, training, and implementing neural networks for real-world applications.", - downloadLink: "https://github.com/avinash201199/Free-programming-books/tree/main/Machine%20Learning", - level: "Advanced", - tags: ["Deep Learning", "Neural Networks", "AI"] -}, -{ - id: "ml-9", - title: "Natural Language Processing with Python", - author: "Steven Bird, Ewan Klein, Edward Loper", - category: "Machine Learning", - language: "Python", - pages: 504, - year: 2009, - description: "Analyzing text with the Natural Language Toolkit. Covers text processing, classification, and information extraction.", - downloadLink: "https://github.com/avinash201199/Free-programming-books/tree/main/Machine%20Learning", - level: "Beginner", - tags: ["NLP", "Python", "NLTK", "Text Processing"] -}, + { + id: "ml-1", + title: "Hands-On Machine Learning", + author: "Aurélien Géron", + category: "Machine Learning", + language: "Python", + pages: 856, + year: 2022, + description: "Practical guide to ML with Scikit-Learn, Keras, and TensorFlow.", + downloadLink: "https://github.com/avinash201199/Free-programming-books/tree/main/Machine%20Learning", + level: "Intermediate", + tags: ["Machine Learning", "Python", "TensorFlow", "Scikit-Learn"], + featured: true + }, + { + id: "ml-2", + title: "Pattern Recognition and Machine Learning", + author: "Christopher Bishop", + category: "Machine Learning", + language: "General", + pages: 738, + year: 2006, + description: "Comprehensive introduction to the fields of pattern recognition and machine learning.", + downloadLink: "https://github.com/avinash201199/Free-programming-books/tree/main/Machine%20Learning", + level: "Advanced", + tags: ["Machine Learning", "Pattern Recognition", "Theory"] + }, + { + id: "ml-3", + title: "Deep Learning", + author: "Ian Goodfellow, Yoshua Bengio, Aaron Courville", + category: "Machine Learning", + language: "General", + pages: 801, + year: 2016, + description: "Deep Learning is one of the most widely recognized and authoritative books covering modern deep learning theory, algorithms, and applications.", + downloadLink: "https://github.com/avinash201199/Free-programming-books/tree/main/Machine%20Learning", + level: "Advanced", + tags: ["Deep Learning", "Neural Networks", "AI"] + }, + { + id: "ml-4", + title: "Machine Learning", + author: "Saikat Dutt, Subramanian Chandramouli, Amit Kumar Das", + category: "Machine Learning", + language: "General", + pages: 741, + year: 2016, + description: "The Beginner textbook on Machine Learning from Pearson.", + downloadLink: "https://github.com/avinash201199/Free-programming-books/tree/main/Machine%20Learning", + level: "Beginner", + tags: ["Machine Learning", "ML", "DS"] + }, + { + id: "ml-5", + title: "Mathematics for Machine Learning", + author: "Marc Peter Deisenroth, A. Aldo Faisal, Cheng Soon Ong", + category: "Machine Learning", + language: "General", + pages: 417, + year: 2020, + level: "All Levels", + description: "the foundational tools and concepts of mathematics needed to understand and develop machine learning algorithms", + downloadLink: "https://github.com/avinash201199/Free-programming-books/blob/main/Machine%20Learning/mathematics%20for%20ml.pdf", + tags: ["MachineLearning", "Mathematics", "Optimization", "MLAlgorithms"], + featured: true + }, + { + id: "ml-6", + title: "The Little Book of Deep Learning", + author: "François Fleuret", + category: "Machine Learning", + language: "General", + pages: 129, + year: 2023, + level: "Intermediate", + description: "A concise and practical introduction to deep learning, covering fundamental concepts, architectures, and techniques in a clear and accessible manner for practitioners and students.", + downloadLink: "https://fleuret.org/public/lbdl.pdf", + tags: ["DeepLearning", "NeuralNetworks", "MachineLearning", "AI", "Practical"], + featured: true + }, + { + id: "ml-7", + title: "Neural Networks", + author: "Simon Haykin", + category: "Machine Learning", + language: "General", + pages: 823, + year: 2005, + description: "Neural Networks: A Comprehensive Foundation is a complete guide to understanding, designing, and applying neural networks in theory and practice.", + downloadLink: "https://github.com/avinash201199/Free-programming-books/tree/main/Machine%20Learning", + level: "Advanced", + tags: ["Deep Learning", "Neural Networks", "AI"] + }, + { + id: "ml-8", + title: "Neural Network Design", + author: "Martin T. Hagan", + category: "Machine Learning", + language: "General", + pages: 1012, + year: 1995, + description: "Neural Network Design by Martin T. Hagan is a practical guide to designing, training, and implementing neural networks for real-world applications.", + downloadLink: "https://github.com/avinash201199/Free-programming-books/tree/main/Machine%20Learning", + level: "Advanced", + tags: ["Deep Learning", "Neural Networks", "AI"] + }, + { + id: "ml-9", + title: "Natural Language Processing with Python", + author: "Steven Bird, Ewan Klein, Edward Loper", + category: "Machine Learning", + language: "Python", + pages: 504, + year: 2009, + description: "Analyzing text with the Natural Language Toolkit. Covers text processing, classification, and information extraction.", + downloadLink: "https://github.com/avinash201199/Free-programming-books/tree/main/Machine%20Learning", + level: "Beginner", + tags: ["NLP", "Python", "NLTK", "Text Processing"] + }, + + { + id: "ml-10", + title: "Understanding Deep Learning", + author: "Simon J.D. Prince", + category: "Deep Learning", + language: "English", + year: 2025, + pages: 541, + level: "Advanced", + description: "A comprehensive textbook providing a detailed and mathematically rigorous introduction to the core concepts, models, and algorithms of deep learning.", + downloadLink: "https://udlbook.com/", + tags: ["Deep Learning", "Creative Commons", "Advanced"] + }, // AI Books { @@ -605,17 +619,17 @@ export const books: Book[] = [ }, { id: "ds-3", - title: "sofware-engineering-9th-edition", - author: "Ian Sommerville", + title: "Julia for Data Science", category: "Data Science", - language: "General", - pages: 832, - year: 2015, - description: "Comprehensive guide to software engineering principles and practices.", - downloadLink: "https://engineering.futureuniversity.com/BOOKS%20FOR%20IT/Software-Engineering-9th-Edition-by-Ian-Sommerville.pdf", - level: "All Levels", - tags: ["Software Engineering", "Principles", "Practices", "Data Science"] - } + language: "Julia", + pages: 339, + author: "Jose Storopoli", + year: 2016, + level: "Intermediate", + description: "A comprehensive guide to using the Julia programming language for data science, covering data manipulation, visualization, and statistical analysis.", + downloadLink: "https://example.com/julia-data-science-2016.pdf", + tags: ["Julia", "Data Science", "Statistics", "Data Manipulation"], + }, // C Programming { @@ -1015,7 +1029,7 @@ export const languages = [ "HTML/CSS", "dart", "General", - "MATLAB" + "Julia" ]; export const levels = ["Beginner", "Intermediate", "Advanced", "All Levels"];