Ultimate Computer Science Encyclopedia by Wahba Eslam (6 results)
Language: English
Published by Independently Published, 2026
- Softcover
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PAP. Condition: New. New Book. Shipped from UK. Established seller since 2000.
Language: English
Published by Independently Published, 2026
- Softcover
Seller: PBShop.store UK, Fairford, GLOS, United KingdomPBShop.store UK
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PAP. Condition: New. New Book. Shipped from UK. Established seller since 2000.
Language: English
Published by Amazon Digital Services LLC - Kdp Apr 2026, 2026
- Softcover
Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH
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Taschenbuch. Condition: Neu. Neuware.
Language: English
Published by Independently Published, 2026
- Softcover
- Print on Demand
Seller: Grand Eagle Retail, Bensenville, IL, U.S.A.Grand Eagle Retail
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Paperback. Condition: new. Paperback. The Only AI & Computer Science Reference You Will Ever NeedTired of juggling twenty books, three courses, and hundreds of blog posts just to understand one concept? This encyclopedia ends that. Over 1,000 pages - from computer science foundations to deploying production LLM systems - organiz…ed so every concept buil2026ds on the last.What's Inside49 Major Topics with complete coverage: CS Foundations, Algorithms, Systems Design, Databases, Cloud/DevOps, Machine Learning, Deep Learning, Generative AI, LLMs, MLOps, Cybersecurity, AI Safety, and Future Technologies335+ Reference Tables comparing algorithms, architectures, cloud services, fairness metrics, and optimization strategies side by side133 Production-Grade Code Examples in Python - DQN, PPO, RAG pipelines, DDP training, LLM guardrails, A/B test calculators, and moreReal-World Case Studies from Netflix, Uber, Google, Meta, and OpenAIPractice Problems with Full Solutions for technical interviews at top AI companiesTopics CoveredFoundations: Boolean logic, Turing machines, P vs NP, CUDA execution model, GPU Tensor Cores, cache timing attacks, JIT compilation, torch.compileML & Deep Learning: Backpropagation derivation, ResNets, transformers, FlashAttention, GQA, RoPE, SwiGLU, knowledge distillation, contrastive learning, MAE, Mamba, state space models, NASGenerative AI & LLMs: GPT/BERT/LLaMA/Mistral/Claude architectures, RLHF, Constitutional AI, DPO, RAG, vector databases, LoRA, QLoRA, AWQ quantization, vLLM, speculative decoding, prompt engineering, agents, tool useMLOps & Systems: Feature stores, model monitoring, drift detection, A/B testing, Kubeflow, SageMaker, Vertex AI, Kubernetes GPU scheduling, KEDA autoscaling, canary deployment, SLOs, error budgetsReinforcement Learning: MDPs, Q-learning, DQN, PPO, SAC, RLHF reward models, reward hacking, offline RL, Decision Transformer, multi-agent RLMathematics: Matrix calculus, Jacobians, convex optimization, KKT conditions, Gaussian processes, information theory, concentration inequalities, PAC learningCloud & DevOps: AWS CDK, Vertex AI Pipelines, Pulumi multi-cloud, spot instance training, FinOps, Docker, Terraform, CI/CD for MLAI Ethics & Governance: EU AI Act, NIST AI RMF, algorithmic fairness, disparate impact, differential privacy, federated learning, AI incident responseWho This Is ForML engineers, data scientists, software engineers transitioning into AI, AI researchers, FAANG interview candidates, and graduate students in CS, Data Science, and Electrical Engineering.Why This Stands ApartEvery topic includes: plain-language explanation, mathematical foundations, production Python code, real-world applications, and comparison tables. No filler. No padding. This is the reference we wish existed when we started building AI systems.2026 Edition - covers LLaMA-3, Claude 3.5, GPT-4o, Mistral, Mamba, DeepSeek-V3, AWS Bedrock, and Vertex AI. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
Language: English
Published by Independently published, 2026
- Softcover
- Print on Demand
Seller: California Books, Miami, FL, U.S.A.California Books
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Language: English
Published by Independently Published, 2026
- Softcover
- Print on Demand
Seller: CitiRetail, Stevenage, United KingdomCitiRetail
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Paperback. Condition: new. Paperback. The Only AI & Computer Science Reference You Will Ever NeedTired of juggling twenty books, three courses, and hundreds of blog posts just to understand one concept? This encyclopedia ends that. Over 1,000 pages - from computer science foundations to deploying production LLM systems - organiz…ed so every concept buil2026ds on the last.What's Inside49 Major Topics with complete coverage: CS Foundations, Algorithms, Systems Design, Databases, Cloud/DevOps, Machine Learning, Deep Learning, Generative AI, LLMs, MLOps, Cybersecurity, AI Safety, and Future Technologies335+ Reference Tables comparing algorithms, architectures, cloud services, fairness metrics, and optimization strategies side by side133 Production-Grade Code Examples in Python - DQN, PPO, RAG pipelines, DDP training, LLM guardrails, A/B test calculators, and moreReal-World Case Studies from Netflix, Uber, Google, Meta, and OpenAIPractice Problems with Full Solutions for technical interviews at top AI companiesTopics CoveredFoundations: Boolean logic, Turing machines, P vs NP, CUDA execution model, GPU Tensor Cores, cache timing attacks, JIT compilation, torch.compileML & Deep Learning: Backpropagation derivation, ResNets, transformers, FlashAttention, GQA, RoPE, SwiGLU, knowledge distillation, contrastive learning, MAE, Mamba, state space models, NASGenerative AI & LLMs: GPT/BERT/LLaMA/Mistral/Claude architectures, RLHF, Constitutional AI, DPO, RAG, vector databases, LoRA, QLoRA, AWQ quantization, vLLM, speculative decoding, prompt engineering, agents, tool useMLOps & Systems: Feature stores, model monitoring, drift detection, A/B testing, Kubeflow, SageMaker, Vertex AI, Kubernetes GPU scheduling, KEDA autoscaling, canary deployment, SLOs, error budgetsReinforcement Learning: MDPs, Q-learning, DQN, PPO, SAC, RLHF reward models, reward hacking, offline RL, Decision Transformer, multi-agent RLMathematics: Matrix calculus, Jacobians, convex optimization, KKT conditions, Gaussian processes, information theory, concentration inequalities, PAC learningCloud & DevOps: AWS CDK, Vertex AI Pipelines, Pulumi multi-cloud, spot instance training, FinOps, Docker, Terraform, CI/CD for MLAI Ethics & Governance: EU AI Act, NIST AI RMF, algorithmic fairness, disparate impact, differential privacy, federated learning, AI incident responseWho This Is ForML engineers, data scientists, software engineers transitioning into AI, AI researchers, FAANG interview candidates, and graduate students in CS, Data Science, and Electrical Engineering.Why This Stands ApartEvery topic includes: plain-language explanation, mathematical foundations, production Python code, real-world applications, and comparison tables. No filler. No padding. This is the reference we wish existed when we started building AI systems.2026 Edition - covers LLaMA-3, Claude 3.5, GPT-4o, Mistral, Mamba, DeepSeek-V3, AWS Bedrock, and Vertex AI. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
