Ebrahim Alareqi's Blog

The qualitative approach to research is  Focused on understanding a phenomenon from a closer perspective.  Done in interviews, open-ended questions, or focus groups.  In most cases, a small number of participants participate in this type of research. Requires many resources and much time. Findings  cannot be generalized to the whole population. Limitations: Cannot generalize to the general population Challenges in applying statistical methods Difficulty in assessing relations between characteristics The quantitative approach   Tends to approximate phenomena from a larger number of individuals using survey methods. T he possibility of summarizing characteristics across groups or relationships. Applies statistical techniques to recognize overall patterns in the relations of processes.  Experimental group and control group. Limitations: Difficulty in recognizing new and untouched phenomena. Caution in interpretation without ...

The idea behind Reinforcement Learning is that an agent will learn from the environment by interacting with it and receiving rewards for performing actions. H umans learn through interaction with the surrounding environment. You drop something, it breaks, you know that you don't have to drop it again. Reinforcement Learning is just a computational approach of learning from action. We don't need to many training sets to learn.We just need occasional feedback that we did the right thing and can then figure out everything else ourselves. This is the task  reinforcement learning  tries to solve. Reinforcement learning lies somewhere in between supervised and unsupervised learning. Whereas in supervised learning one has a target label for each training example and in unsupervised learning one has no labels at all, in reinforcement learning one has  sparse  and  time-delayed  labels – the rewards. Based only on those rewards the agent has to learn...

While working on your dissertation, you will be overwhelmed with references as they increase in number and reference managing becomes cumbersome. Choosing a good reference manager is another problem because when you start writing, it might be difficult to change the software, so you need to choose the best one from the very beginning. I personally used the three software listed down. My favorite one was -and still- Zetero. Zotero is the only software that automatically senses research on the web [and has a plug-in with Chrome]. Zotero is very helpful when you need an article say from JSTOR,  a preprint from arXiv.org or even a news story from the New York Times or a book from a library. Try it and let me know in the comments. Zotero See Zotero's  video tutorials here , or browse the  user guides . Mendeley Watch the  video tutorials  or visit the  help guides  to learn more. EndNote Each software...

We want the latest operating systems, phones and tech. Our Education system has been around since 1900. Our Education system is outdated. We live in the information age. This Education model is based on linearity, conformity( compliance with standards, rules, or laws ), and batching people, it's obsolete. Whatever you learn at the beginning of the university years is obsolete by the time you graduate. Peter Diamandis said, "There will be as many changes between 2016-2022 due to exponential technology growth as between 1900-2000". more than %2000 growth. This is just the beginning of the exponential growth. Many of the jobs we have didn't exist 5 years ago. (Cloud computing specialist, 3D printing professionals, Digital Marketing specialist, Vlogger, Chief Listening Officer, Drone Operator, Social Media Marketer,  SEO Specialist, UX Designer, Big Data Analysts), We don't live in the age of standardization, we live in the age of Customization. Anybody can teach t...

If you have an interest in computer hardware and software but you aren’t sure which career path to choose, you probably want to learn about information technology (IT) and computer science. These two rewarding careers each require a slightly different set of skills, and they each appeal to a somewhat different type of person. An IT career involves installing, organizing and maintaining computer systems as well as designing and operating networks and databases. Computer science is focused entirely on efficiently programming computers using mathematical algorithms. An IT career doesn’t necessarily require a computer science (CS) degree, although a CS degree opens certain doors that otherwise wouldn’t be available. IT professionals typically work in a business environment installing internal networks and computer systems and perhaps programming. Computer scientists work in a wider range of environments, ranging from businesses to universities to video game design companies. Both o...

For many data scientists, the largest limitation of Python is that all data must fit into the resident memory of the available workstation. Further, traditionally, Python has only been able to utilize one CPU. Data scientists constantly ask, "How can I read and process large amounts of data?" and "How can I make use of more computational processing resources?" This blog will introduce you to Dask, a flexible parallel computing library for analytic computing. With Dask, you will be able to take the Python workflows you currently have and easily scale them up to large datasets on your workstation without the need to migrate to a distributed computing environment. We can think of Dask at a high and a low level:  High-level collections: Dask provides high-level Array, Bag, and DataFrame collections that mimic NumPy, lists, and Pandas but can operate in parallel on datasets that don't fit into main memory. Dask's high-level collections are alternatives to ...

If you are interested in Twitter and want some nice Python script that will help you do the work than this book is for you. Download