The Shallow and the Deep is a collection of lecture notes that …
The Shallow and the Deep is a collection of lecture notes that offers an accessible introduction to neural networks and machine learning in general. However, it was clear from the beginning that these notes would not be able to cover this rapidly changing and growing field in its entirety. The focus lies on classical machine learning techniques, with a bias towards classification and regression. Other learning paradigms and many recent developments in, for instance, Deep Learning are not addressed or only briefly touched upon.
Biehl argues that having a solid knowledge of the foundations of the field is essential, especially for anyone who wants to explore the world of machine learning with an ambition that goes beyond the application of some software package to some data set. Therefore, The Shallow and the Deep places emphasis on fundamental concepts and theoretical background. This also involves delving into the history and pre-history of neural networks, where the foundations for most of the recent developments were laid. These notes aim to demystify machine learning and neural networks without losing the appreciation for their impressive power and versatility.
This resource is a video abstract of a research paper created by …
This resource is a video abstract of a research paper created by Research Square on behalf of its authors. It provides a synopsis that's easy to understand, and can be used to introduce the topics it covers to students, researchers, and the general public. The video's transcript is also provided in full, with a portion provided below for preview:
"The sustainability of the terrestrial ecosystem depends on the stability of its tiniest residents. The terrestrial microbiome controls functions such as organic carbon turnover, nutrient-use efficiency, and productivity, and losing critical keystone functions may cause dramatic shifts in microbiome composition and function. A recent study sought to better understand the relationship between biodiversity and microbiome stability. Researchers inoculated microbial communities differing in phylogenetic diversity into sterilized soil and evaluated the resulting microbiome stability. They found that bacterial communities with higher phylogenetic diversity tended to be more stable throughout a range of pH values. Specialized metabolic functions, including “nitrogen metabolism” and "phosphonate and phosphinate metabolism,” were identified as keystone functions. These critical functions were carried out by specific bacterial taxa, including Nitrospira and Gammatimonas..."
The rest of the transcript, along with a link to the research itself, is available on the resource itself.
This resource is a video abstract of a research paper created by …
This resource is a video abstract of a research paper created by Research Square on behalf of its authors. It provides a synopsis that's easy to understand, and can be used to introduce the topics it covers to students, researchers, and the general public. The video's transcript is also provided in full, with a portion provided below for preview:
"Bacteriophages are everywhere, influencing everything from microbial evolution to biogeochemical cycling. Phages, however, remain among the least understood members of complex microbiomes. Do the tools used to identify phages introduce biases? A recent study compared ten of the most widely used bioinformatics tools designed to detect phages from metagenomics data. Overall, tool performance varied substantially in the analysis of different benchmarking datasets. For a set of artificial RefSeq contigs, PPR Meta and VirSorter2 showed the highest performance. Kraken2 showed the highest accuracy for a mock community benchmark. And generally, k-mer tools performed better than similarity- or gene-based tools. The study offers insight into the biases introduced by different tools, offers guidance into which one is best suited for different use cases, and suggests that rather than relying on any one tool, researchers may do well to combine different ones to suit their research needs..."
The rest of the transcript, along with a link to the research itself, is available on the resource itself.
This resource is a video abstract of a research paper created by …
This resource is a video abstract of a research paper created by Research Square on behalf of its authors. It provides a synopsis that's easy to understand, and can be used to introduce the topics it covers to students, researchers, and the general public. The video's transcript is also provided in full, with a portion provided below for preview:
"As a precursor to biobased chemicals, biomass holds enormous potential for meeting the needs of the circular economy. To get the most out of biomass, a new study proposes borrowing tools from machine learning. During anaerobic fermentation, biomass fuels the growth and proliferation of various microorganisms. These microbes, in turn, form organic molecules that can be processed into specialty chemicals, but the conditions and microbes most conducive to this process aren’t always known. To find out, researchers examined bioreactors designed to form medium-chain carboxylates from xylan and lactate. As expected, reducing the hydraulic retention time, or the average time soluble compounds reside in a bioreactor, boosted the formation of useful medium-chain carboxylates. The key was to identify the organisms responsible for this boost. For that, the team used machine learning models designed to link the change in hydraulic retention time to distinct sequences of microbial DNA..."
The rest of the transcript, along with a link to the research itself, is available on the resource itself.
This resource is a video abstract of a research paper created by …
This resource is a video abstract of a research paper created by Research Square on behalf of its authors. It provides a synopsis that's easy to understand, and can be used to introduce the topics it covers to students, researchers, and the general public. The video's transcript is also provided in full, with a portion provided below for preview:
"Some commercial fish species have both wild and farmed populations. Distinguishing between them is important for identifying escaped fish, managing food safety risk, and setting appropriate market prices. However, for many species, suitable genetic markers haven’t yet been discovered. To provide an alternative, researchers recently tried to use gut microbiome data to differentiate between wild and farmed large yellow croaker. Compared with those of wild croaker, the rectums of farmed croaker had lower microbial diversity (Shannon index values) and bacterial loads, and different microbiome compositions that were distinguishable despite high inter-batch variability. For example, the wild fish microbiome was dominated by _Psychrobacter_ spp., while the farmed fish microbiome was not. The predicted functions of the gut microbes also differed between wild and farmed croaker, presumably because the populations have divergent diets and thus divergent gut environments..."
The rest of the transcript, along with a link to the research itself, is available on the resource itself.
This resource is a video abstract of a research paper created by …
This resource is a video abstract of a research paper created by Research Square on behalf of its authors. It provides a synopsis that's easy to understand, and can be used to introduce the topics it covers to students, researchers, and the general public. The video's transcript is also provided in full, with a portion provided below for preview:
"Viruses that infect bacteria and archaea are abundant in human and environmental microbiomes. Their roles in manipulating, killing, and recycling microbes makes them key players in environmental processes and human health and disease, including inflammatory bowel diseases. In spite of their importance, the tools available for analyzing viral genomes are limited. Now, a new tool allows researchers to identify viruses and predict their functions using genomic data. VIBRANT (Virus Identification By iteRative ANnoTation), is the first software to use a hybrid machine learning and protein similarity approach. going beyond traditional limitations to maximize the identification of highly diverse viruses. In validation experiments with reference datasets, VIBRANT recovered higher-quality virus sequences and reduced false identification of non-viral genome fragments compared to other identification programs..."
The rest of the transcript, along with a link to the research itself, is available on the resource itself.
The organizations that depend largely on collecting data from various sources or …
The organizations that depend largely on collecting data from various sources or are highly digitized must adopt data security. It is better to fight the risks at the initial stage than to regret the loss of data and face the consequences. If the information can not be kept safe from various attacks then the preference of the organization will decrease eventually. Even if personal information cannot be trusted in the hands of the organization then there will be dissatisfaction among customers. If an organization is unable to keep its customers satisfied then its value can hit rock bottom. Hence, by using Artificial Intelligence and Machine Learning the data security should be made better. These technologies will also help in decreasing the extra effort that has to be put by an organization and its employees.
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