Estimated delivery 3-12 business days
Format Paperback
Condition Brand New
Description The final chapter of the book introduces Transformers, a revolutionary model that has had a significant impact on natural language processing (NLP).
"Deep Learning for Data Architects" is a comprehensive guide that bridges the gap between data architecture and deep learning. It provides a solid foundation in Python for data science and serves as a launchpad into the world of AI and deep learning. The book begins by addressing the challenges of transforming raw data into actionable insights. It provides a practical understanding of data handling and covers the construction of neural network-based predictive models. The book then explores specialized networks such as convolutional neural networks (CNNs), recurrent neural networks (RNNs), and generative adversarial networks (GANs). The book delves into the theory and practical aspects of these networks and offers Python code implementations for each.
Shekhar Khandelwal is a distinguished Senior AI & Data Scientist, residing in the bustling harbor city of Hamburg, Germany. His academic career shines bright with a Master's degree in Data Science, achieving distinction for his thesis work in the realm of Computer Vision. His name can be spotted in top-tier research papers and publications, predominantly in the area of Deep Learning.
Grand Eagle Retail is the ideal place for all your shopping needs! With fast shipping, low prices, friendly service and over 1,000,000 in stock items - you're bound to find what you want, at a price you'll love!
Shipping is FREE to any address in USA.
Please view eBay estimated delivery times at the top of the listing. Deliveries are made by either USPS or Courier. We are unable to deliver faster than stated.
International deliveries will take 1-6 weeks.
NOTE: We are unable to offer combined shipping for multiple items purchased. This is because our items are shipped from different locations.
If you wish to return an item, please consult our Returns Policy as below:
Please contact Customer Services and request "Return Authorisation" before you send your item back to us. Unauthorised returns will not be accepted.
Returns must be postmarked within 4 business days of authorisation and must be in resellable condition.
Returns are shipped at the customer's risk. We cannot take responsibility for items which are lost or damaged in transit.
For purchases where a shipping charge was paid, there will be no refund of the original shipping charge.
If you have any questions please feel free to Contact Us.