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Discussion 1

Technology Mega Trends For 21st-century enterprises, connectivity, big data and analytics, and digitization are technology mega trends that cannot be ignored. Business breakthroughs and innovation would be impossible without them. They also mark the difference between outdated 20th-century business models and practices and those of today’s on-demand economy.
One of the things that has been in the headlines recently is COVID-19. Recent developments surrounding the COVID-19 global pandemic have had a far-reaching effect on the global economy and the professional and personal lives of individuals. Consequently, companies in all industry sectors have had to act much more quickly to create new business models that address the regulatory requirements of COVID-19 lockdowns along with ensuing health and safety concerns and new purchasing habits of consumers, vendors and partners. Most companies have achieved this goal primarily by integrating new innovative information and communication technologies into their business models to increase personal engagement with consumers, vendors and partners, maintain a competitive advantage in the market and develop the operational resilience needed to safeguard their sustainability. As a result, the rate of digital transformation around the globe has increased significantly.
Research a company or area of your choice such as education, healthcare, law enforcement, retail, social media, etc. and discuss the impact COVID-19 had on them and what they did about it.

Computer Science Question

Find a peer-reviewed scholarly journal article discussing blockchain technology. Complete a review of the article by writing a 2-3 page overview of the article. This will be a detailed summary of the journal article, including concepts discussed and findings. Additionally, find one other source (it does not have to be a peer-reviewed journal article) that substantiates the findings in the article you are reviewing.
Your paper should meet these requirements:
Be approximately three to four pages in length, not including the required cover page and reference page.
Follow APA 7 guidelines. Your paper should include an introduction, a body with fully developed content, and a conclusion.
Support your answers with the readings from the course and at least two scholarly journal articles to support your positions, claims, and observations,
Be clearly and well-written, concise, and logical, using excellent grammar and style techniques.


Computer Science Assignment Help Many new products’ inventions we see today in the market come from unmet needs for customers. Entrepreneurs look for gaps in the market and try to invent the right product or service to fulfill the gap for customers.
Review lecture materials and assigned readings and write a minimum 1.5 (450 words) page, APA formatted paper discussing three (3) major inventions that have led to successful products

This is just the first 2 chapters of the thesis. More work will follow on this same thesis over

This is just the first 2 chapters of the thesis.
More work will follow on this same thesis over the next 2 weeks.

Study area: Computer Science Research Area: Improving the accuracy rate and training time of Stochastic Gradient Descent Algorithm on Convolutional Neural Networks. Brief Overview : To explore the several optimization techniques available for deep learning networks like CNN, and attempt to apply a strategic weight refinement maneuver with GSGD to the most commonly used optimization techniques for CNN. The aim of this research is to significantly improve prediction accuracies when compared to the canonical variants of the machine learning optimization techniques. The effective application of GSGD will realize the significance of inconsistencies on gradient computation in deep learning networks and aim to perform gradient computation and weight update using only consistent data. The algorithm will attempt to hide the inconsistencies present in the large training datasets for deep learning networks considering that it may become consistent over the next few iterations. While this enhancement comes at a cost of delay in network training, this research will further enhance the CNN-GSGD algorithm by parallelizing the gradient computation process in deep learning CNN to speed up the training process. I have already got proof of concept program code and favourable results in this research area. Thesis outline: Chapter 1: Big Data, Deep Learning, Neural Networks, Convolutional Neural Networks, Chapter2 : Optimization Algorithms, Gradient Descent Algorithms, Stochastic Gradient Descent Algorithm Chapter 3: I already have a published conference paper which would form basis of chapter 3. It involves addition of a strategic weight refinement maneuvre to Stochastic Gradient Descent Algorithms for ConvolutionalNeuralNetworks. This maneuvre will act as a guide to SGD Algorithms which results in improved accuracy rates. Chapter 4: the same maneuvre is now parallelized and applied. Discuss drawbacks of previous chapter~ while improving accuracy it makes the training time longer. Solution is to parallelize thr strategic weight refinement maneuvre that I discussed in chapter 3. For reference and help ij writing this chapter , I will provide an additional paper which was applied to logistic regression and you can refer same concept being applied to Convolutional Neural Networks Chapter 5: Overall discussions and benefit of approach discussed in the thesis. Closing remarks and conclusion. References.

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