Pengantar Machine Learning

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Buku Ajar Pengantar Deep Learning Dalam Pemrosesan Citra

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Author : Rian Rahmanda Putra
language : id
Publisher: Penerbit NEM
Release Date : 2023-04-11

Buku Ajar Pengantar Deep Learning Dalam Pemrosesan Citra written by Rian Rahmanda Putra and has been published by Penerbit NEM this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-04-11 with Business & Economics categories.

Buku Ajar Pengantar Deep Learning dalam Pemrosesan Citra memberikan pemahaman ringkas bagi mahasiswa yang akan mendalami Deep Learning. Di dalam buku ini membahas bagaimana proses konvolusi dari suatu model sehingga dapat mengetahui citra yang dimaksud. Materi yang dibahas dalam buku ini meliputi Konsep Dasar Artificial Intelligence, Pengenalan Machine Learning, Deep Learning dan Image Processing, Pengenalan IDE Google Colaboratory, Dataset Preparation, Hyperparameter Tuning, Studi Kasus (Binary Classification), dan Studi Kasus (Multiclass Classification). Semoga dengan hadirnya buku ini dapat memberikan kontribusi khususnya dalam keilmuan di bidang informatika.

Pengantar Deep Learning Algoritma Dan Studi Kasus

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Author : Prof. Dr. Ermatita, Dr. Vina Ayumi, Dr. Handrie Noprisson, Dr. Mariana Purba, Feby Ardianto, M.Cs, Muhammad Adrezo, M.Sc.
language : id
Publisher: CV Jejak (Jejak Publisher)
Release Date : 2025-05-17

Pengantar Deep Learning Algoritma Dan Studi Kasus written by Prof. Dr. Ermatita, Dr. Vina Ayumi, Dr. Handrie Noprisson, Dr. Mariana Purba, Feby Ardianto, M.Cs, Muhammad Adrezo, M.Sc. and has been published by CV Jejak (Jejak Publisher) this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-05-17 with Antiques & Collectibles categories.

Buku "Pengantar Deep Learning: Algoritma dan Studi Kasus" dirancang sebagai panduan komprehensif untuk memahami konsep dan implementasi deep learning. Buku ini sangat cocok untuk mahasiswa, peneliti, dan praktisi yang ingin mendalami Deep Learning secara teori dan praktik. Buku ini adalah buku ajar yang mata kuliah deep learning. Bahasan pokok dari buku ini antara lain Pendahuluan, Convolutional Neural Network, MobileNets, Inception, VGG, ResNet, Optimasi Model, Evaluasi Kinerja dan Beberapa Studi Kasus, yang masing-masing dijelaskan dari segi konsep dan cara kerjanya. Buku ini juga membahas teknik optimasi model seperti Dropout, L2-Regularization, Batch Normalization, dan Data Augmentation yang dirancang untuk membantu pembaca meningkatkan performa model. Pada bagian evaluasi kinerja, pembaca akan mempelajari metrik-metrik utama seperti akurasi, precision, recall, F1-score, dan confusion matrix, yang sangat penting untuk mengevaluasi keberhasilan model. Keunggulan utama buku ini adalah studi kasus praktis menggunakan dataset CIFAR-10. Pembaca akan dipandu melalui proses pengembangan model, mulai dari persiapan dataset, pembuatan arsitektur model, hingga evaluasi dan finalisasi model. Beberapa studi kasus lain juga membahas pengembangan model baseline, penerapan regularisasi, hingga teknik peningkatan performa menggunakan kombinasi metode.

Machine Learning

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Author : Janeman Sumah
language : id
Publisher: Serasi Media Teknologi
Release Date : 2025-06-17

Machine Learning written by Janeman Sumah and has been published by Serasi Media Teknologi this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-06-17 with Computers categories.

Buku ini membahas tentang Machine learning yang merupakan cabang dari kecerdasan buatan (artificial intelligence/AI) yang memungkinkan komputer untuk belajar dari data dan meningkatkan kinerjanya tanpa diprogram secara eksplisit. Dalam machine learning, algoritma digunakan untuk menganalisis data, mengenali pola, dan membuat prediksi atau keputusan berdasarkan data tersebut. Proses ini melibatkan pelatihan model dengan dataset, kemudian mengujinya untuk mengukur akurasi prediksi. Machine learning terbagi menjadi tiga jenis utama: supervised learning, unsupervised learning, dan reinforcement learning. Aplikasi machine learning sangat luas, mulai dari rekomendasi produk di e-commerce, deteksi penipuan, pengenalan wajah, hingga kendaraan otonom. Dengan kemajuan teknologi dan ketersediaan data besar (big data), machine learning menjadi semakin penting dalam kehidupan modern.

Machine Learning

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Author : Giandari Maulani, S.Kom, M.Kom
language : id
Publisher: MEGA PRESS NUSANTARA
Release Date : 2025-03-15

Machine Learning written by Giandari Maulani, S.Kom, M.Kom and has been published by MEGA PRESS NUSANTARA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-03-15 with Computers categories.

Buku MACHINE LEARNING ini mengupas salah satu inovasi teknologi yang telah mengubah cara kita hidup, bekerja, dan berinteraksi dengan dunia di sekitar kita. Machine learning tidak hanya menjadi fondasi dari berbagai kemajuan teknologi, tetapi juga membuka jalan bagi transformasi di berbagai sektor, mulai dari kesehatan, keuangan, hingga pendidikan. Melalui pembelajaran berbasis data. teknologi ini memberikan kemampuan untuk memahami pola-pola kompleks. membuat prediksi akurat, dan mengotomasi proses yang sebelumnya hanya dapat dilakukan oleh manusia. Ditulis dengan pendekatan yang lugas dan mudah dipahami, buku ini tidak hanya menjelaskan prinsip-prinsip di balik machine learning, tetapi juga menyajikan wawasan tentang dampak sosial, etika, dan masa depan teknologi ini. Dengan kemampuannya yang terus berkembang, machine learning telah menjadi motor penggerak di balik inovasi seperti mobil tanpa pengemudi, asisten virtual, dan sistem rekomendasi yang semakin cerdas. Namun, di balik segala potensinya, terdapat tantangan dan pertanyaan besar yang perlu dijawab: Bagaimana kita memastikan teknologi ini bermanfaat bagi semua orang? Apa dampaknya pada dunia kerja? Dan sejauh mana kita dapat mempercayai mesin untuk membuat keputusan penting? Buku ini mengundang pembaca untuk memasuki dunia yang penuh kemungkinan, di mana data menjadi bahan bakar utama, dan algoritma menjadi arsitek perubahan. Lebih dari sekadar panduan teknis, MACHINE LEARNING adalah eksplorasi mendalam tentang bagaimana manusia dan mesin dapat bekerja bersama untuk menciptakan masa depan yang lebih baik. Melalui pemahaman yang mendalam tentang teknologi ini, Anda tidak hanya akan dibekali dengan pengetahuan, tetapi juga dengan perspektif baru tentang peran Anda dalam era kecerdasan buatan. Selami potensi tanpa batas dari MACHINE LEARNING dan jadilah bagian dari revolusi yang sedang berlangsung-di mana inovasi bukan lagi sekadar kemungkinan, tetapi sebuah keharusan untuk masa depan.

Artificial Intelligence Machine Learning And Deep Learning

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Author : Oswald Campesato
language : en
Publisher: Mercury Learning and Information
Release Date : 2020-01-23

Artificial Intelligence Machine Learning And Deep Learning written by Oswald Campesato and has been published by Mercury Learning and Information this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-01-23 with Computers categories.

This book begins with an introduction to AI, followed by machine learning, deep learning, NLP, and reinforcement learning. Readers will learn about machine learning classifiers such as logistic regression, k-NN, decision trees, random forests, and SVMs. Next, the book covers deep learning architectures such as CNNs, RNNs, LSTMs, and auto encoders. Keras-based code samples are included to supplement the theoretical discussion. In addition, this book contains appendices for Keras, TensorFlow 2, and Pandas. Features: Covers an introduction to programming concepts related to AI, machine learning, and deep learning Includes material on Keras, TensorFlow2 and Pandas

Pengenalan Praktis Supervised Machine Learning Dengan Jupyter Notebook

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Author : Yudha Nurdin, Khairun Saddami, Nasaruddin
language : id
Publisher: USK Press
Release Date : 2025-03-26

Pengenalan Praktis Supervised Machine Learning Dengan Jupyter Notebook written by Yudha Nurdin, Khairun Saddami, Nasaruddin and has been published by USK Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-03-26 with Education categories.

Buku ajar ini disusun sebagai pendukung beberapa mata kuliah di antaranya Kecerdasan Artifisial, Machine Learning, dan Deep Learning untuk memberikan pemahaman dasar bagi mahasiswa/i tentang teknik pembelajaran mesin terawasi menggunakan Jupyter Notebook. Supervised machine learning atau pembelajaran mesin terawasi merupakan salah satu metode yang banyak digunakan dalam berbagai aplikasi, mulai dari analisis data hingga pengembangan kecerdasan artifisial. Dengan Jupyter Notebook, pengguna dapat memanfaatkan lingkungan interaktif untuk mengembangkan dan mengeksplorasi model machine learning dengan mudah dan efisien. Buku ajar ini diawali dengan konsep dasar supervised machine learning, gambaran praktis hingga penerapannya menggunakan Jupyter Notebook. Dalam pembahasannya, kami menyajikan contoh-contoh sederhana yang dapat diikuti oleh pemula untuk memulai eksplorasi lebih lanjut dalam bidang ini. Kami berharap buku ini dapat memberikan manfaat bagi pembaca yang tertarik dalam dunia pembelajaran mesin, khususnya yang ingin memahami dasar-dasar penggunaan Jupyter Notebook dalam implementasi model-model supervised machine learning.

Memahami Konsep Dan Implementasi Machine Learning

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Author : Prihandoko Prihandoko
language : id
Publisher: PT. Sonpedia Publishing Indonesia
Release Date : 2024-02-17

Memahami Konsep Dan Implementasi Machine Learning written by Prihandoko Prihandoko and has been published by PT. Sonpedia Publishing Indonesia this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-02-17 with Computers categories.

Buku Memahami Konsep dan Implementasi Machine Learning ini, menyajikan materi yang lengkap mulai dari Dasar-dasar Machine Learning, Pengumpulan dan Pemrosesan Data, Algoritma Machine Learning Populer, Evaluasi Model dan Tuning, Implementasi Machine Learning Serta Etika dan Tanggung Jawab dalam Machine Learning. Manfaat dari buku ini diharapkan digunakan sebagai pondasi utama dalam pembelajaran Machine Learning lanjutan. Buku ini Penulis rancang secara sistematis yang dapat digunakan sebagai referensi dalam pembelajaran machine learning.

Practical Approach For Machine Learning And Deep Learning Algorithms

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Author : Pandey Abhishek Kumar
language : en
Publisher: BPB Publications
Release Date : 2019-09-20

Practical Approach For Machine Learning And Deep Learning Algorithms written by Pandey Abhishek Kumar and has been published by BPB Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-09-20 with Computers categories.

Guide covering topics from machine learning, regression models, neural network to tensor flow Key features Machine learning in MATLAB using basic concepts and algorithms. Deriving and accessing of data in MATLAB and next, pre-processing and preparation of data. Machine learning workflow for health monitoring. The neural network domain and implementation in MATLAB with explicit explanation of code and results. How predictive model can be improved using MATLAB? MATLAB code for an algorithm implementation, rather than for mathematical formula. Machine learning workflow for health monitoring. Description Machine learning is mostly sought in the research field and has become an integral part of many research projects nowadays including commercial applications, as well as academic research. Application of machine learning ranges from finding friends on social networking sites to medical diagnosis and even satellite processing. In this book, we have made an honest effort to make the concepts of machine learning easy and give basic programs in MATLAB right from the installation part. Although the real-time application of machine learning is endless, however, the basic concepts and algorithms are discussed using MATLAB language so that not only graduation students but also researchers are benefitted from it.What will you learn Pre-requisites to machine learning Finding natural patterns in data Building classification methods Data pre-processing in Python Building regression models Creating neural networks Deep learning Who this book is forThe book is basically meant for graduate and research students who find the algorithms of machine learning difficult to implement. We have touched all basic algorithms of machine learning in detail with a practical approach. Primarily, beginners will find this book more effective as the chapters are subdivided in a manner that they find the building and implementation of algorithms in MATLAB interesting and easy at the same time.Table of contents1. Pre-requisite to Machine Learning2. An introduction to Machine Learning3. Finding Natural Patterns in Data4. Building Classification Methods5. Data Pre-Processing in Python6. Building Regression Models7. Creating Neural Networks8. Introduction to Deep LearningAbout the authorAbhishek Kumar Pandey is pursuing his Doctorate in computer science and done M.Tech in Computer Sci. & Engineering. He has been working as an Assistant professor of Computer Science at Aryabhatt Engineering College and Research center, Ajmer and also visiting faculty in Government University MDS Ajmer. He has total Academic teaching experience of more than eight years with more than 50 publications in reputed National and International Journals. His research area includes- Artificial intelligence, Image processing, Computer Vision, Data Mining, Machine Learning. His Blog: http://veenapandey.simplesite.com/His LinkedIn Profile: https://www.linkedin.com/in/abhishek-pandey-ba6a6a64/ Pramod Singh Rathore is M. Tech in Computer Sci. and Engineering from Government Engineering College Ajmer, Rajasthan Technical University, Kota, India. He have been working as an Assistant Professor Computer Science at Aryabhatt Engineering College and Research center, Ajmer and also a visiting faculty in Government University Ajmer. He has authored a book in Network simulation which published worldwide. He has a total academic teaching experience more than 7 years with many publications in reputed national group, CRC USA, and has 40 publications as Research papers and Chapters in reputed National and International E-SCI SCOPUS. His research area includes machine learning, NS2, Computer Network, Mining, and DBMS. Dr S. Balamurugan is the Head of Research and Development, Quants IS & CS, India. Formely, he was the Director of Research and Development at Mindnotix Technologies, India. He has authored/co-authored 33 books and has 200 publications in various international journals and conferences to his credit. He was awarded with Three Post-Doctoral Degrees- Doctor of Science (D.Sc.) degree and Two Doctor of Letters(D.Litt) degrees for his significant contribution to research and development in Engineering, and is the recepient of thee Best Director Award, 2018. His biography is listed in "e;World Book of Researchers"e; 2018, Oxford, UK and in "e;Marquis WHO'S WHO"e; 2018 issue, New Jersey, USA. He carried out a healthcare consultancy project for VGM Hospitals between 2013 and 2016, and his current research projects include "e;Women Empowerment using IoT"e;, "e;Health-Aware Smart Chair"e;, "e;Advanced Brain Simulators for Assisting Physiological Medicine"e;, "e;Designing Novel Health Bands"e; and "e;IoT -based Devices for Assisting Elderly People"e;. His LinkedIn Profile: https://www.linkedin.com/in/dr-s-balamurugan-008a7512/

Dasar Dan Konsep Machine Learning

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Author : Feri Sulianta
language : id
Publisher: Feri Sulianta
Release Date : 2025-07-12

Dasar Dan Konsep Machine Learning written by Feri Sulianta and has been published by Feri Sulianta this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-07-12 with Computers categories.

Buku ini berisi panduan komprehensif mengenai Machine Learning (ML), sebuah cabang dari kecerdasan buatan (AI) yang memungkinkan sistem untuk belajar dari data dan pengalaman untuk meningkatkan performa tanpa pemrograman eksplisit. Dimulai dengan pengenalan tentang dasar-dasar kecerdasan buatan, buku ini menyelami berbagai teknik dan algoritma dalam Machine Learning, seperti pembelajaran terawasi (supervised learning), pembelajaran tidak terawasi (unsupervised learning), dan pembelajaran penguatan (reinforcement learning). Didalamnya juga membahas alat dan framework yang digunakan dalam pengembangan model ML, dengan penekanan pada Python sebagai bahasa pemrograman pilihan. Pembaca akan diperkenalkan dengan pustaka-pustaka Python populer seperti NumPy, Pandas, TensorFlow, dan Keras, serta teknik-teknik dasar dalam pengembangan model ML, seperti pengumpulan data, pembersihan data, transformasi fitur, hingga optimasi model. Buku ini tidak hanya membahas teori, tetapi juga memberikan contoh implementasi nyata dalam berbagai aplikasi kehidupan sehari-hari, dari sistem rekomendasi hingga mobil otonom.

Ai Crash Course

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Author : Hadelin de Ponteves
language : en
Publisher: Packt Publishing Ltd
Release Date : 2019-11-29

Ai Crash Course written by Hadelin de Ponteves and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-11-29 with Computers categories.

Unlock the power of artificial intelligence with top Udemy AI instructor Hadelin de Ponteves. Key FeaturesLearn from friendly, plain English explanations and practical activitiesPut ideas into action with 5 hands-on projects that show step-by-step how to build intelligent softwareUse AI to win classic video games and construct a virtual self-driving carBook Description Welcome to the Robot World ... and start building intelligent software now! Through his best-selling video courses, Hadelin de Ponteves has taught hundreds of thousands of people to write AI software. Now, for the first time, his hands-on, energetic approach is available as a book. Starting with the basics before easing you into more complicated formulas and notation, AI Crash Course gives you everything you need to build AI systems with reinforcement learning and deep learning. Five full working projects put the ideas into action, showing step-by-step how to build intelligent software using the best and easiest tools for AI programming, including Python, TensorFlow, Keras, and PyTorch. AI Crash Course teaches everyone to build an AI to work in their applications. Once you've read this book, you're only limited by your imagination. What you will learnMaster the basics of AI without any previous experienceBuild fun projects, including a virtual-self-driving car and a robot warehouse workerUse AI to solve real-world business problemsLearn how to code in PythonDiscover the 5 principles of reinforcement learningCreate your own AI toolkitWho this book is for If you want to add AI to your skillset, this book is for you. It doesn't require data science or machine learning knowledge. Just maths basics (high school level).