DataScience-MachineLearning-PythonEntwickler Portfolio

Twitter Medium

• Analysis of tweets posted about Angela Merkel for a short period (about 10 days) on twitter
• Use of tools such as pandas and matplotlib for discovery data analysis
• Normal and masked visualization with WordCloud
• Calculate the percentage of negative subject distributions by language
• NLP processing (text cleaning-vectorization-tokenization)
• Machine learning model development with 1500 labeled tweets
• Label estimation of 650 twitt test data

• Searching for rising locations that investors can target and professional points for new business acquisitions.
• To solve this business problem, we are going to cluster Manchester neighborhoods to suggest places where homeowners can invest in real estate and the current average property price.
• To explore and target recommended locations across different venues according to the presence of amenities and essential facilities, we will access data through FourSquare API interface and arrange them as a dataframe for visualization.
• Neighborhoods are analyzed to offer real estate for home buyers to invest.
• The k-mean clustering technique is used because it is fast and efficient in terms of computation cost.

• Thanks to pandas a"Correlation Analysis" between world happiness report and covid-19 infected numbers
• Some changes experienced by countries in the epidemic are analyzed
• The maximum number of infected and the countries are combined in a single list against the happiness index
• Positive correlation with seaborn

• Review and evaluate the twitter data set
• Data discovery
• Removing unnecessary words and punctuation marks
• Tokenization processes
• Creating a suitable pipline
• Model development with naive bayes
• Evaluating test results

• Housing Sales Prices & Venues Data Analysis of Manchester
• What Did Trump and Biden Say About Each Other On Twitter-Bot Accounts Generated By Their Artificial
• Using Keras Tokenizer Class for Text Preprocessing Steps — 1st Presidential Debate Transcript 2020
• Create A News Summarizer With Python And NLP
• 10 Tasks With NLP: Twitter Sentiment Analysis
• An NLP Analysis: What is Happening About the Presidents on Twitter?
• Revolutionize in Python with CatBoost
• Machine Learning Applied to Time Series
• Time Series Analysis Types for Machine Learning Applications (With Examples)

• Development of Smart Plate Number Recognition System for Fast Cars With Python
• Masking With WordCloud in Python: 500 Most Frequently Used Words in German
• 5-Steps Guide to Parallel Processing in Python
• A Guide To Creating An Automatic Mail Sending System With Python
• What Are The Best & Popular Python Frameworks
• 5 Steps To Understanding Generators In Python
• Coding A Simple Game Model By Creating Functions In Python: “Three Cup Monte”
• 5 Steps to Understanding Polymorphism in Python
• Learn Decorators in Python in 5 Steps
• Understanding Character Encoding in Python
• 7 Examples of Understanding Recursion Functions in Python
• The Best Way to Understand Composition in Python: 5 Case Studies and Solution
• Contribution of ‘Padding’ in Python for NLP Projects

• Visualization on the Map Using Starbucks Store Locations in Germany
• What Does Covid-19 and World Happiness Report Data Tell Us?
• How Possible Is It Now to Predict US Elections With Data Analysis?
• How Were The Predictions For The Coronavirus In October Confirmed?

• Google - Technical Support Fundamentals
• IBM - Applied Data Science Capstone
• IBM - Data Analysis with Python
• IBM - Data Science Methodology
• IBM - Data Science
• IBM - Databases and SQL for Data Science
• IBM - Tools for Data Science
• IBM- Data Visualization with Python
• IBM- Machine Learning with Python
• IBM- Python for Data Science and AI
• IBM- What is Data Science
• John Hopkins University - The Data Scientist's Toolbox
• Michigan University - Python Data Structures
• Michigan University - Python for everybody
• NLP in TensorFlow - - deeplearningcom
• Python HackerRank Certificate
• Python Bootcamp From Zero to Hero in Python
• University of California - SQL for Data Science
• Zertifikat - DIGITALES LEBEN UND ARBEITEN 4.0
• Google - Crash Course on Python