Robert Colby – författare

Comprehensive overview of the fledgling domain of federated learning (FL), explaining emerging FL methods, architectural approaches, enabling frameworks, and applications

Model Optimization Methods for Efficient and Edge AI explores AI model engineering, evaluation, refinement, optimization, and deployment across multiple cloud environments (public, private, edge, and hybrid). It presents key applications of the AI paradigm, including computer vision (CV) and Natural Language Processing (NLP), explaining the nitty-gritty of federated learning (FL) and how the FL method is helping to fulfill AI model optimization needs. The book also describes tools that vendors have created, including FL frameworks and platforms such as PySyft, Tensor Flow Federated (TFF), FATE (Federated AI Technology Enabler), Tensor/IO, and more.

The first part of the text covers popular AI and ML methods, platforms, and applications, describing leading AI frameworks and libraries in order to clearly articulate how these tools can help with visualizing and implementing highly flexible AI models quickly. The second part focuses on federated learning, discussing its basic concepts, applications, platforms, and its potential in edge systems (such as IoT).

Other topics covered include:

Building AI models that are destined to solve several problems, with a focus on widely articulated classification, regression, association, clustering, and other prediction problemsGenerating actionable insights through a variety of AI algorithms, platforms, parallel processing, and other enablersCompressing AI models so that computational, memory, storage, and network requirements can be substantially reducedAddressing crucial issues such as data confidentiality, data access rights, data protection, and access to heterogeneous dataOvercoming cyberattacks on mission-critical software systems by leveraging federated learning

Written in an accessible manner and containing a helpful mix of both theoretical concepts and practical applications, Model Optimization Methods for Efficient and Edge AI is an essential reference on the subject for graduate and postgraduate students, researchers, IT professionals, and business leaders.

Comprehensive overview of the fledgling domain of federated learning (FL), explaining emerging FL methods, architectural approaches, enabling frameworks, and applications Model Optimization Methods for Efficient and Edge AI explores AI model engineering, evaluation, refinement, optimization, and deployment across multiple cloud environments (public, private, edge, and hybrid). It presents key applications of the AI paradigm, including computer vision (CV) and Natural Language Processing (NLP), explaining the nitty-gritty of federated learning (FL) and how the FL method is helping to fulfill AI model optimization needs. The book also describes tools that vendors have created, including FL frameworks and platforms such as PySyft, Tensor Flow Federated (TFF), FATE (Federated AI Technology Enabler), Tensor/IO, and more. The first part of the text covers popular AI and ML methods, platforms, and applications, describing leading AI frameworks and libraries in order to clearly articulate how these tools can help with visualizing and implementing highly flexible AI models quickly. The second part focuses on federated learning, discussing its basic concepts, applications, platforms, and its potential in edge systems (such as IoT). Other topics covered include: Building AI models that are destined to solve several problems, with a focus on widely articulated classification, regression, association, clustering, and other prediction problemsGenerating actionable insights through a variety of AI algorithms, platforms, parallel processing, and other enablersCompressing AI models so that computational, memory, storage, and network requirements can be substantially reducedAddressing crucial issues such as data confidentiality, data access rights, data protection, and access to heterogeneous dataOvercoming cyberattacks on mission-critical software systems by leveraging federated learningWritten in an accessible manner and containing a helpful mix of both theoretical concepts and practical applications, Model Optimization Methods for Efficient and Edge AI is an essential reference on the subject for graduate and postgraduate students, researchers, IT professionals, and business leaders.

Comprehensive overview of the fledgling domain of federated learning (FL), explaining emerging FL methods, architectural approaches, enabling frameworks, and applications

Model Optimization Methods for Efficient and Edge AI explores AI model engineering, evaluation, refinement, optimization, and deployment across multiple cloud environments (public, private, edge, and hybrid). It presents key applications of the AI paradigm, including computer vision (CV) and Natural Language Processing (NLP), explaining the nitty-gritty of federated learning (FL) and how the FL method is helping to fulfill AI model optimization needs. The book also describes tools that vendors have created, including FL frameworks and platforms such as PySyft, Tensor Flow Federated (TFF), FATE (Federated AI Technology Enabler), Tensor/IO, and more.

The first part of the text covers popular AI and ML methods, platforms, and applications, describing leading AI frameworks and libraries in order to clearly articulate how these tools can help with visualizing and implementing highly flexible AI models quickly. The second part focuses on federated learning, discussing its basic concepts, applications, platforms, and its potential in edge systems (such as IoT).

Other topics covered include:

Building AI models that are destined to solve several problems, with a focus on widely articulated classification, regression, association, clustering, and other prediction problemsGenerating actionable insights through a variety of AI algorithms, platforms, parallel processing, and other enablersCompressing AI models so that computational, memory, storage, and network requirements can be substantially reducedAddressing crucial issues such as data confidentiality, data access rights, data protection, and access to heterogeneous dataOvercoming cyberattacks on mission-critical software systems by leveraging federated learning

Written in an accessible manner and containing a helpful mix of both theoretical concepts and practical applications, Model Optimization Methods for Efficient and Edge AI is an essential reference on the subject for graduate and postgraduate students, researchers, IT professionals, and business leaders.

''''You asked my business,'''' remarked Dasher, ''''and I told you that I’m a trouble-shooter. I shoot trouble - with this.'''' He waved the .45. ''''And you’re trouble. My client asked that you both be removed, and I’m most obliging, you see, at a price.''''''''Why?'''' cried Marian. ''''Why should he want us killed?''''''''I don’t know,'''' said Dasher. ''''I have no idea. Those things are never of interest to me. I have clients all over the country who send people to me. I never ask why. I ask, how much will you pay? That’s what I ask. Some people come higher than others. It depends on their importance. And believe me, this is not an expensive job, as they go. You’ll hardly be missed.''''He called to his assistant. ''''Go get the tarp. The gentleman will go first. I’m in no hurry with the lady.'''' He gave Marian a lewd grin.

She put her head on my shoulder. Her hand slid off my thigh and into my lap, paused. She kissed my ear, lingered there. ''''And what are you afraid of?'''' she whispered.''''Afraid you’ll stop,'''' I said against the moist spread of her lips.''''I couldn’t,'''' she answered, falling back on the divan, taking me with her. ''''Not for a long, long time,'''' she said beside me. She took my hand and guided it beneath her sweater to the warmth of bare breast. ''''Feel my heart,'''' she said. ''''I’m a fast train on a down track to nowhere. And my heart says ''Couldn’t stop-wouldn’t stop-couldn’t if I would-wouldn’t if I could . . .

Her fortune was the price on her headBurt Keating had been trying to make the acquaintance of his pretty red-headed neighbor, but he wasn’t getting very far - until the day she escaped from a strange roadside encounter. For when it turned out that murder had resulted from the affair, she threw herself hysterically into Burt’s arms, pleading for his help.It seems she had inherited a sealed box, whose contents were entirely unknown. Certain parties wanted that box badly. They had offered her a fortune - or sudden death.Burt knew then that chivalry can go too far, for there was no longer any way out once he’d tangled with the quaking widow.

For Ross Elliot the summer held no promise. With his teaching duties over until fall, he found himself facing boredom, with time on his hands. Which was why he didn’t hesitate to involve himself in the affairs of one Barbara Erickson, ex-student and accused murderess.As far as Elliot was concerned it simply wasn’t possible for one so young - and so lovely - to be capable of such a horrendous crime. And what if he was the only one who believed in her innocence? A couple of months playing private-eye would be just the change of pace he needed.But after he had started poking around a little, Ross Elliott began to wonder if he really was a very good judge of character. And when someone started taking pot-shots at him, he knew he still might be bored that summer - right through the heart with a .38 bullet!

Driving to Miami, Scott Daniels paused to rescue a lady in distress. She was in a road house, abandoned by her date, and so Scott offered Valerie a lift. No sooner had they started off, then they spotted the boyfriend’s car smashed in an accident. Valerie begged Scott to save her good name by salvaging her suitcase from the wreck before the cops could find it. But no sooner had he done so, then he learned that instead of being filled with pink unmentionables, it was loaded with green negotiables - hundreds of thousands of them.Curiosity being stronger than caution, Scott kept his eye on Valerie after dropping her off in Miami. And thus found himself the only element remaining between a gang of ruthless criminals and the perfect crime.

For twelve long years they remembered. For twelve long years they plotted. And now Captain Driscoll was going to pay for what he had done to them during the war.They weren’t going to kill him right away. First there would be only little things, irritating things, that would build and grow and tighten until Captain Driscoll became afraid. Then they’d begin their reign of terror. That would be the best part. The three revenge-hungry men would savor those moments like a good wine.And when Captain Driscoll was a broken, sobbing man, when his sanity was almost gone, they would murder him.

There were seven of them, that white-hot summer at Malibu, with seven different deadly desires, each primed for explosion - and each focused on the destruction-hungry woman named Star Osborne.

And then there were five . . .

Howie was a millionaire and he and Andrea were planning to be married. But he never got to walk to the altar - he was murdered first.All five of Andrea’s lovers were suspects - Doug, Jeff, Ralph, Mark, and Bud. And the motive was clear. But only Andrea knew what impelled her to take her life in her hands and spend one night with each of them after the murder . . .

It started like most of Marian’s troubles, because of her betting the ponies - that consuming habit which she herself could hardly understand.Someone told her once that she wanted to lose. But Marian knew that was nonsense. She wanted to win, win, win!This time when Marian lost, she became desperate. Her husband, Warren Emrick, refused to give her the money - even though he had $48,000 stashed away.So when Tony Viani, an ex-playmate, turned up offering to pay her debt, Marian was in the mood to betray her husband. In a gesture of spite she took Warren’s money and ran off with Tony.Only Marian didn’t figure on Warren’s need for revenge or Tony’s lust for power. And that’s when her trouble really started . . .troubles that filled her days and nights with violence and terror.

Tormented by a satin-skinned package of dynamite who offered him ecstasy unfettered by convention . . . Bedeviled by another woman who wanted a master . . . Given 12 hours to get out of town - and then framed for murder.This was the grim situation faced by Todd Corwin shortly after he came to Longport seeking Julie Steadman’s killer.If he cleared out of town he was sure of safety. If he stayed, nothing was certain except more trouble with the police and a deepening involvement with the Vollmer clan -Austin, who owned everything in town including the cops . . . Joy, Austin’s wife, who took men where she found them . . . and Gail, the step-daughter, who would risk anything to take Todd away from Joy.

Kim affected men like an electric current. And she usually set off the charge. But when Eddie Tarino took her for a cruise on his yacht, she was like a little girl at the zoo - outside the leopard’s cage.Tarino’s yacht parties were wild - featuring every kind of vice. But before this one was over, Kim had tamed the leopard - and was a full-fledged member of a strange and savage jungle . . .

Bonnie wanted only one thing: Big money. She had everything she needed to get it - a body that tormented men and an air of sensual excitement that teased as it promised. She was available - for a price.Until she met Larry Duggan, whose animal magnetism reduced her to a state of slavish adoration. Her need consumed her, night and day.And then the party started to get rough. . .

Barry Lunsford was down on his luck. He had no money, no girl and a lousy job. Then he found $300,000 in stolen cash. But his brief fling in paradise was shattered by the two vicious hoods who wanted the money back. They gave him a choice: return the cash or they’d carve Iris up into little pieces and feed her to the fish. It was his move.