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AWS Machine Learning Scholarship Program

https://www.udacity.com/scholarships/aws-machine-learning-scholarship-program?bsft_eid=bc85a78a-5d43-4e0c-5683-0f6e5336ecb1&utm_campaign=sch_600_2020-04-30_ndxxx_aws-ml-pre-reg-announcement_global&utm_source=blueshift&utm_medium=email&utm_content=sch_600_2020-04-30_ndxxx_aws-ml-pre-reg-announcement_global&bsft_clkid=4a1b2411-3bcd-4ccf-974a-23562b20e7e6&bsft_uid=6e0e8d28-5982-44df-b0e5-45e388c364e0&bsft_mid=2e378f52-c942-4dde-966a-37664fbc4cb8&bsft_ek=2020-04-30T21:02:38Z&bsft_mime_type=html

#StayHome #PreventCOVId19 #LearnMachineLearning

Thanks for your participation in the Q&A poll. The answer is double asterisks(**)

Example: print(2 ** 3) is 8. 2 the power of 3.

Ask @pyDiscussion if you have any question.
#QuarantineYourself #LearnPython #LearnDataScience

The death rate of Somalia and Sudan is high when we compare others. Ethiopia is in good status. Almost 50% are recovered in #Djiboti
#QuarantineYourself #LearnDataScience

6 Reasons Now’s the Perfect Time to Commit to Coding




https://news.codecademy.com/6-reasons-to-learn-to-code/?utm_source=customer_io&utm_medium=email&utm_campaign=worker_support&utm_content=6reasons

Jupyter Notebooks

Jupyter Notebooks are an extremely powerful tool for data analysis because they allow you to run python commands and see outputs within the structure of a notebook, which is helpful because in Data Analysis you are often running short commands to produce the data/visualizations you need for a certain investigation.

To know how to install Jupyter notebook, looking at the following short video

https://www.youtube.com/watch?v=5Yx6h7Mgiv0

Learn Python 3 the Hard Way

@python4fds

Sometimes I share you some python books which may help you to study python. Because #PYTHON is the powerful tool for Data Science, Machine Learning, Artificial Intelligence, and also to develop desktop application, web application etc. Ask @pydiscussion

#Python is a multi-paradigm, dynamically typed, multipurpose programming language, designed to be quick (to learn, to use, and to understand), and to enforce a clean and uniform syntax. Please note that Python 2 is officially out of support as of January 1, 2020. Therefore automatically shift yourself from Python-2 to the latest and most improved version of python [python-3.x] .

#QuarantineYourself #LearnPython #LearnDataScience

Reading a File using Python

Computers use file systems to store and retrieve data. Each file is an individual container of related information. If you’ve ever saved a document, downloaded a song, or even sent an email you’ve created a file on some computer somewhere. Even script.py, the Python program you’re editing in the learning environment, is a file.
So, how do we interact with files using Python?
Let’s say we had a file called hello_python.txt with these contents:

Python is a powerful tool for Data Ananlysis. So, stay at home and learn python for future Data Science.

We could read that file like this:

script.py

with open('hello_python.txt') as python_file:
python_contents = python_file.read()
print(python_contents)

This
opens a file object called python_file and creates a new indented block where you can read the contents of the opened file. We then read the contents of the file python_file using python_file.read() and save the resulting string into the variable python_contents. Then we print python_contents, which outputs the statement written in the above!.

#QuarantineYourself #LearnPython #LearnDataScience

Introduction to Machine Learning

The year is 2049…
But learn Python then Data Science(Data Analyze, Data Manipulation, Visualization, and Hypothesis testing), and then Learn Machine Learning.
Finally, learn AI

Python is a general-purpose programming language. It can do almost all of what other languages can do with comparable, or faster, speed. It is often chosen by Data Analysts and Data Scientists for prototyping, visualization, and execution of data analyses on datasets.

There’s an important question here. Plenty of other programming languages, like R, can be useful in the field of data science. Why are so many people choosing Python?

One major factor is Python’s versatility. There are over 125,000 third-party Python libraries. These libraries make Python more useful for specific purposes, from the traditional (e.g. web development, text processing) to the cutting edge (e.g. AI and machine learning). For example, a biologist might use the Biopython library to aid their work in genetic sequencing.

Additionally, Python has become a go-to language for data analysis. With data-focused libraries like pandas, NumPy, and Matplotlib, anyone familiar with Python’s syntax and rules can use it as a powerful tool to process, manipulate, and visualize data.

#FaceMask #KeepDistancing #LearnPython #LearnDataScience

Join @python4fds for more information

Machine Learning

Machine Learning is the science of getting computers to learn and act like humans do, and improve their learning over time in autonomous fashion, by feeding them data and information in the form of observations and real-world interactions. It has taken the Data Science world by storm.

It can be branched out into the following categories:

Supervised Learning
Unsupervised Learning

Supervised Learning is when the data is labeled and the program learns to predict the output from the input data. For instance, a supervised learning algorithm for credit card fraud detection would take as input a set of recorded transactions. It would learn what makes a transaction likely to be fraudulent. Then, for each new transaction, the program would predict if it is fraudulent or not.

Unsupervised Learning is where the data is unlabeled and the program learns to recognize the inherent structure of the input data. For the same fraud example, the model would take in a bunch of transactions with no indication of if they are fraudulent or not, and it would group them based on patterns it sees. It might discover two groups, fraudulent and legitimate.
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#DataScience #MachineLearning