FREE COURSES IN MACHINE LEARNING

In our aim of sharing our delights with you all, while continuing with our theme of Machine Learning and the Artificial Intelligence Revolution, OMNITEKK is enthused to imbue our fellow technophiles with free courses on the foundations of Machine Learning. 

And for all interested, we sure hope you enjoy the journey.

Until our next I.T. adventure my friends, OMNITEKK says be well.

Machine Learning Regression And Classification

https://www.coursera.org/learn/machine-learning

Introduction To Machine Learning

https://www.classcentral.com/course/youtube-introduction-to-machine-learning-dmitry-kobak-2020-21-46773

Statistical Machine Learning

https://www.classcentral.com/course/youtube-statistical-machine-learning-ulrike-von-luxburg-2020-46771

Mathematics For Machine Learning

https://www.classcentral.com/course/youtube-mathematics-for-machine-learning-ulrike-von-luxburg-2020-21-46772

DATA SCIENCE

The means by which we categorize and classify data streams of structural inputs is at the heart of the Data Science revolution.

As such, Data Science and its explorations, help us to gain critical insights into statistical attributes pertaining to the fields of social sciences and human behavioral trends, patternistic archaeological inferences and deductions within the animal world, as well as helping us to discover breakthrough advances in healthcare and the pharmaceutical industry, in effort to support human longevity.

Likewise, there are a few key trends in the field that help data scientists working with larger data-sets organize and make efficient use of the information gathered, so as to advance the field, and utilize the  proficiencies gained within structured data models, to better understand the evolutionary progressions of our species and our world.

These Trends Include -

WEB SCRAPING AND DATA MINING 

in effort to develop statistical trends and deep attributional correlations between seemingly disjointed information. 

If we seek to deduce an assertion from within a particular attribute of interest, the larger the data set or volume of information we collect, the greater the chance of doing so becomes. 

Data mining and data collection is an essential area of data science in that it is the foundational source of information and digital data statistical deduction.

DATA ANALYSIS 

We come to know things based on the means by which we classify and define them.

Data analysis helps us accomplish this, through a series of hypothetical assertions and tests that allow scientists, mathematicians, programmers, statisticians and even philosophers alike, to determine the critical or prevalent attributes of a thing, so as to satisfy a specific or particular categorization and determination surrounding it. 

Data analysis includes gathering pertinent key information from a collection of data sources whether clustered, structured or unstructured to be used in such a determination.

INFERENTIAL INDUCTION AND DEDUCTION

Most of the information we collect is usually geared toward discovering an inferred hypothesis or deducing the refutation thereof. 

The process of drawing correlations between data stores, allow such inferences to be either proved or disproved upon gaining a better understanding of the trends that either affirm or disprove inferences of observation that serve as the foundational learning curves in discovering how certain attributes connect with critical theories, or the lack thereof.

MACHINE LEARNING 

Once critical analytical derivations have commenced, the definitive classification of either a model of regression or progression pertaining to a specific data sample, either serves as a dimensionality attribute of an existing data model or the foundational key attribute of the deep learning required to successfully classify a new one through attributional clustering.

In essence, machine learning is the attributional process of either creating, adjoining or declassifying data such that definitive categorizations and determinations of recognition might be made upon future interaction with it, based on inferential statistical and mathematical calculations of correlation or contrast.

DATA VISUALIZATION 

A key vestige in the world of Data Science lie in being able to convey technical or otherwise complex structural data concepts in easy to understand ways. 

This my friends, is where data visualization models come in to play.

Data visualization is the process of pictorially showcasing statistical attributional findings, so as to convey significance or minimizations pertaining to a specific concept, field, or area of study. 

Graphs, Data Decision Trees, Charts and even Videographical Data Displays, are all frequently used data visualization tools.

ACCUMULATIVE INSIGHTS OF ATTRIBUTIONAL EVOLUTION 

Once each of the stages in the data science process commences, the means by which attributional evolutionary variations across the classification spectrum is structured, should be continually measured or quantified, to record classification progression.

Here variances are traced, analyzed, and re-categorized where necessary, to maintain integrity in categorical attributional accuracy.

It's no secret that our world has vastly become a data-driven machine where the answer to some of our most pressing phenomena might be enclosed within the deep vestiges of digital data structures.

As such, Data Science field progressions once considered difficult and cumbersome to gauge attributional certainty in, now prove quite effortless, albeit tools such as machine learners and information access leverages of usable structured and unstructured data, that help us advance in understanding our world and the esoteric wonders within it...

...all thanks to improved Data Science measures.

We sure hope you've enjoyed our walk down Data Science Lane, and until our next I.T. adventure my friends, OMNITEKK says be well.

CYBERCRIME

The INTERNET OF THINGS has made way for the invaluable vestiges of e-commerce, global connectedness, as well as productivity to increase demonstrably, as collaborative and convenience solutions are right at our fingertips.

Likewise, the evolution of such avenues have also allowed CYBER CRIMINALS to utilize these dais in effort to carry out harmful aim against unsuspecting machine users in undeniable fashion, spawning the exponential emergence of crime prevention measures.

CYBERCRIME includes any and all acts to steal, deceive, and terrorize both personal and organizational machine users alike, in effort to cause significant harm...

...to include -

Spoofing identifying machine information to garner trust and gain unauthorized access to someone's machine and machine resources.

Stealing personal information to use illicitly, such as banking information, passports and other identifying information to commit cyber crimes.

Using Spyware to acquire the 'Digital Fingerprint' of machine users for the purposes of illegally tracking internet activity.

Cyber Espionage to elicit brute force attacks by way of preventing access to resources by machine owners to ransom monies or other leverages.

Cyber Terrorism serving as machine owner harassing hubs by breaking valuable resources in effort to garner complicity or to prevent productivity and proficient resource utilization, through acts of cyber violences.

As the means by which our world becomes more connected enhances, so too does the methods criminals have at their disposal to engage in stealthy illegal activities.

Further, the array of faceless and nameless cyber criminals hiding behind machines while using them to steal, terrorize, and force modes of espionage onto unsuspecting targets have far greater aim in absconding their activities from the law, as internet traffic and ports of origin and destination aren't as easily tracked as we might believe, making it an arduous task for cyber crime prevention efforts to successfully identify criminal origins.

As such, one of the best things we can do as machine users is to seek the help of cybersecurity professionals upon observing resource compromisation when first recognized.

Likewise, OMNITEKK suggests keeping a dossier of any and all anomalous circumstances so as to help bring awareness of trends in what you may be facing.

And lastly, it is central to note that even the craftiest cyber criminals eventually get caught.

So be sure to continue your due diligence in helping maintain a safe and secure computing experience for us all.

And until our next I.T. adventure my friends, OMNITEKK says be well.

 

 

LEARNING MACHINES

Computer programs, once sequenced as the functional output of human directives manifesting lightning speed result-sets, have shape-shifted in their nature, as advanced machine processing methods encompass the technological ebbs and flow of machine learning.

The machines of new, given the desired result-set of a given function, now have the "intelligence" to design the relative data inputs themselves to satisfy it.

ARTIFICIAL INTELLIGENCE and MACHINE LEARNING have made way not only for immense productivity levels in our workflows to commence, but have likewise spawned a new era of computing, with the machine itself now having the ability to transform its own instruction sets to accomplish imperceptible successive aim in data mining models, such that our means of both organizing and relating collections of seemingly disjointed information might be used in meaningful ways as we bear witness to the 5th generation of digital networking.

As such, OMNITEKK found a few phenomenal videos to help you understand the key concepts within computational autonomy and the world of MACHINE LEARNING.

Enjoy!

And until our next I.T. adventure my friends, OMNITEKK says be well.