Buku ini disusun untuk memberikan pemahaman yang komprehensif tentang konsep, algoritma, serta implementasi Deep Learning dalam berbagai skenario nyata. Melalui buku ini pembaca akan diperkenalkan pada dasar-dasar jaringan saraf tiruan (Neural networks), optimasi model, hingga arsitektur canggih seperti CNN, RNN dan Transformer. Berbagai framework modern seperti TensorFlow, PyTorch dan Hugging …
Buku ini terdiri atas beberapa bab, antara lain Pemrograman, Runtunan, Percabangan, Pengulangan, Fungsi, Rekursif, Array, Pengurutan, Pencarian, List, Stack, Queue, dan Tree. Buku ini ditujukan bagi para mahasiswa/i Jurusan Teknik Informatika yang ingin belajar dari dasar. Namun, tidak menutup kemungkinan bagi siapa saja pembaca yang mau belajar pemrograman komputer lewat buku ini sebagai refer…
Algorithms that work with deep learning and big data are getting better and better at doing more and more things: They quickly and accurately produce information, and are learning to drive cars more safely and reli- ably than humans.
This ï¬rst volume of the new Interdisciplinary Excellence Accelerator Series (IDEAS) is the ï¬rst major outcome of more than a year of joint work with its inception in a 2-day publishing lab workshop with researchers from the Excellence Cluster “Internet of Production†at RWTH Aachen (Germany) and editors from Springer held in March 2021.
More than politeness, it is a matter of intellectual integrity to warmly thank those who helped me become the author of this book. To begin with, I would like to express my deepest gratitude to the members of the computer science laboratory who let me follow their day-to-day activities. Having an ethnographer around for more than two years must have been an odd experience.
Artiï¬cial Intelligence is now everywhere and fuels both industry and daily life all over the world. We are in the era of “big data,†and huge sums of information can be obtained which are too cumbersome for people to process themselves. These big data are even with much complex correlations behind them in various areas, such as computer vision and social media. For example, the…
The Digital Earth project has been an exciting and very valuable journey, to create a step-change in connecting data science and Earth system sciences. We had unique and intense collaboration between eight centers of the Helmholtz Association in the ï¬eld of Earth and Environment. Our success would not have been possible without the support and dedication of several individuals.