[{"_1":2,"_46":-5,"_47":-5},"loaderData",{"_3":4,"_14":15,"_44":-5,"_45":-5},"root",{"_5":-5,"_6":-5,"_7":-5,"_8":9,"_10":11},"user","shoppingCartId","toast","locale","en","constants",{"_12":13},"paypalClientId","AenrHU49peF-ZUH-Yq7AXLLNZYGUGlml474U16NCjB4ZznmQCEjiliN3whyuVZmkb7VxEzmTALgtKEKE","routes/_store+/_readers+/email_author.$slug/route",{"_16":17,"_43":-5},"book",{"_18":19,"_20":21,"_22":23,"_24":25,"_26":27,"_28":29},"id","Z2lkOi8vbGVhbnB1Yi9TdG9yZTo6Qm9va1Byb2R1Y3QvNjA1OTc","title","Introduction to Deep Learning","state","published","contactAuthorMethod","email","aboutText","

\"Introduction to Deep Learning\" is a bilingual guide created to make AI concepts accessible to a diverse audience. Written in English and Myanmar, it bridges the gap for learners facing language barriers and limited resources.

It covers foundational neural networks, Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), and advanced topics like Transformers and Generative AI. Each chapter blends theory with practical application, emphasizing hands-on learning through Python code snippets and real-world case studies on image classification, time series prediction, and sentiment analysis.

This book aims to support learners at various levels, providing practical insights and resources, including a website and public GitHub repository. \"Introduction to Deep Learning\" is designed to help readers from different backgrounds gain a solid understanding of AI.

","authors",[30],{"_18":31,"_32":33,"_5":34},"Z2lkOi8vbGVhbnB1Yi9TdG9yZTo6UHJvZHVjdEF1dGhvci82NDEyOA","name","myothida",{"_35":36},"avatar",{"_37":38,"_39":40,"_41":42},"url","https://d308did4coypzi.cloudfront.net/avatars/2904839/medium/iSTARLogo.jpg?1676105520","styleName","medium","exists",true,"currentUser","routes/_store+/_layout","routes/_store+/_readers+/_layout","actionData","errors"]

Email the Author