How to scrapping telegram users data and analyzing the data using Pandas

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#Names #Variable #Python
Q: Explain the difference between name and variable in Python?

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#Keynote #Variables #Names
variables are objects stored in memory.
Names are labels that we assign to them. Names are how we refers to variables through code.
Ex: a = 5
a is the name that points to a variable in a memory. There can be possible that multiple names points to the same variable.
Variables keep track of the information we need to successfully execute a program. Variables can be used to store a variety of types of information in computer memory.

IoT
# part 1
What is IOT ❓
The Internet of Thing is network of physical object or '' things '' embedded with electronics, software, sensors & network connectivity. which enables this objects the collect or exchange data.
✅''Things'' in the IoT sense can refer in wide variety of device such as heart monitoring implants, biochip transponders on farm animal, electrical clams in costal waters, automobiles built in sensors.
✅This device collect useful data the help of variety existing technologies and then autonomously flow the data b/n other devices.
How it's work ❓
✅ IoT is not the result of single novel technology instead several complementary technical developments provides capabilities that taken together help to Bering the gap b/n virtual and physical world. The capabilities include :-
-communication & cooperation
- addressability
- identification
- sensing
- actuation
- embedded information processing
- localization
- user interface
#The structure of IoT
The IoT can be viewed as a gigantic network consisting of network of device and computers connected a series of intimidate technologies where numerous technology RFID(radio frequency identification ) wireless connection may act as enables of connectivity.
°Tagging Things: real time items traceability and addressability by RFID
°Feeling Things: sense act as primary device to collect data from the environment.
°Shrinking Things: miniaturization and nanotechnology has providing the ability of small things to interact and connect with '' things '' or '' smaller device ''
°Thinking Things: embedded intelligence in device through sensors has formed the network connection to internet. It can make '' things '' realizing the intelligent control.
© @FTYOTORAWI

# part 2
IoT
How big is the IoT ❓
✅Big and getting bigger -- there are already more connected things than people in the world.

✅Tech analyst company IDC predicts that in total there will be 41.6 billion 👀 connected IoT devices by 2025, or "things." It also suggests industrial and automotive equipment represent the largest opportunity of connected "things,", but it also sees strong adoption of smart home and wearable devices in the near term.  
Benefit of IoT for business ❓
✅it's depend on the particular implementation; agility and efficiency are usually top considerations. The idea is that enterprises should have access to more data about their own products and their own internal systems, and a greater ability to make changes as a result.
For ex:Manufacturers are adding sensors to the components of their products so that they can transmit data back about how they are performing.
Security on IoT ❓
✅Security is one the biggest issues with the IoT. These sensors are collecting in many cases extremely sensitive data -- what you say and do in your own home, for example. Keeping that secure is vital to consumer trust, but so far the IoT's security track record has been extremely poor. Too many IoT devices give little thought to the basics of security, like encrypting data in transit and at rest
The IoT and cyberwarfare ❓
✅The IoT makes computing physical. So if things go wrong with IoT devices, there can be major real-world consequences -- something that nations planning their cyberwarfare strategies are now taking into account.

© @FTYOTORAWI

#KeyNote #DataScience #Methodology #DataMining

Data Science Methodologies

What is CRISP-DM(Cross industries - Data Mining)?

The CRISP-DM methodology is a process aimed at increasing the use of data mining over a wide variety of business applications and industries. The intent is to take case specific scenarios and general behaviors to make them domain neutral. CRISP-DM is comprised of six steps with an entity that has to implement in order to have a reasonable chance of success.

The six steps are shown in the following diagram:

1. Business Understanding:- This stage is the most important because this is where the intention of the project is outlined. Foundational Methodology and CRISP-DM are aligned here. It requires communication and clarity. The difficulty here is that stakeholders have different objectives, biases, and modalities of relating information. They don’t all see the same things or in the same manner. Without clear, concise, and complete perspective of what the project goals are resources will be needlessly expended.

2. Data Understanding:- Data understanding relies on business understanding. Data is collected at this stage of the process. The understanding of what the business wants and needs will determine what data is collected, from what sources, and by what methods. CRISP-DM combines the stages of Data Requirements, Data Collection, and Data Understanding from the Foundational Methodology outline.

3. Data Preparation:- Once the data has been collected, it must be transformed into a useable subset unless it is determined that more data is needed. Once a dataset is chosen, it must then be checked for questionable, missing, or ambiguous cases. Data Preparation is common to CRISP-DM and Foundational Methodology.

4. Modeling:- Once prepared for use, the data must be expressed through whatever appropriate models, give meaningful insights, and hopefully new knowledge. This is the purpose of data mining: to create knowledge information that has meaning and utility. The use of models reveals patterns and structures within the data that provide insight into the features of interest. Models are selected on a portion of the data and adjustments are made if necessary. Model selection is an art and science. Both Foundational Methodology and CRISP-DM are required for the subsequent stage.

5. Evaluation:- The selected model must be tested. This is usually done by having a pre-selected test, set to run the trained model on. This will allow you to see the effectiveness of the model on a set it sees as new. Results from this are used to determine efficacy of the model and foreshadows its role in the next and final stage.

6. Deployment:- In the deployment step, the model is used on new data outside of the scope of the dataset and by new stakeholders. The new interactions at this phase might reveal the new variables and needs for the dataset and model. These new challenges could initiate revision of either business needs and actions, or the model and data, or both.

CRISP-DM is a highly flexible and cyclical model. Flexibility is required at each step along with communication to keep the project on track. At any of the six stages, it may be necessary to revisit an earlier stage and make changes. The key point of this process is that it’s cyclical; therefore, even at the finish you are having another business understanding encounter to discuss the viability after deployment. The journey continues.

For more information on CRISP-DM, go to: IBM Knowledge Center – CRISP-DM Help Overview

“Python 3.9.0 is the newest feature release of the #python3 language” that comes with numerous features, and optimizations.

Hands-On Genetic Algorithms with Python (2020)
Автор: Eyal Wirsansky

📊 How is Machine Learning used in the LinkedIn Recruiter Recommendation System

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Learn new libraries of Python 3.9.0 https://docs.python.org/3/library/stdtypes.html
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#ChallengeMersenneNumber #DataStructure #List #ProgramFlow #Python

- A Mersenne number is any number that can be written as 2^p - 1 for some p. For example, 3 is a Mersenne number (2^2 - 1) as is 31 (2^5 - 1).

- Write a function that accepts an exponent p and returns the corresponding Mersenne number.

Note: Mersenne numbers can only be prime if their exponent, p, is prime. Make a list of the Mersenne numbers for all primes p between 3 and 65 (there should be 17 of them).

Hint: It may be useful to define the is_prime and get_primes functions for use in this problem.

N.B: define a function that accepts an exponent and returns the corresponding Mersenne number. Test the execution time of your algorithm before submitting to this challenge.

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Create GUI Applications with Python & Qt5 (2020)

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