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Felhasználó avatár
$10 USD / óra
INDONESIA zászlója
indonesia
$10 USD / óra
Itt jelenleg ennyi az idő: 5:17 du.
Ekkor csatlakozott: november 11, 2014
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Rizky S.

@kyemaniak

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$10 USD / óra
INDONESIA zászlója
indonesia
$10 USD / óra
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Data Analysis, ML, & Data Visualization

I will find any insights or find a problem solution through analyze your data. Send me your CSV / Excel files, describe what do you want/problems, and i will give you a complete report about how data analysis can be the answer of your problem. I did several data analysis projects using machine learning and statistic before, to find the answer of these kind of questions : 1. What is the common mistakes when user input data into the web? 2. Why the manufacture stock is always negative in site A? 3. Which data entry is detected as a fraud? 4. Why in absence/attendance data, there are several employee that came to the office in a midnight? I am a data enthusiast with excellent skills in data analysis and data visualization. Some tools that I've work with to make a comprehensive data analysis : - Python libraries (Pandas, numpy, scikit-learn, matpotlib, seaborn, etc) - Keras - SQL Server - Excel Data visualization tools : - Power BI
Freelancer Python Developers Indonesia
Az összes Python Developers mutatása itt: Indonesia

Keresse Rizky S. felhasználót a munkájával kapcsolatban

Jelentkezzen be, hogy chaten keresztül megbeszélhessék a részleteket.

Portfólió

4132891
My client has a web application which their partners must manually input the daily actual material stock into the application. My job was made a quantitative data analysis report to answer several questions based on the data : 1. Which data was not input correctly? 2. Which partner was not periodically input the data? 3. find a model that made a prediction if the data input was true or full of manipulation? 4. Find partners that not operate material distribution with a legal procedure To answer these questions, here was what i did : 1. make integration and collect needed data from SQL Server database, and put it as a pandas dataframe 2. pick the right features to answer the questions 3. Did several statistic and machine learning works using pandas & scikit-learn 4. Make a report in PDF 5. Client Presentation For the result, my client successfully update their application design, that improve the quality of the data that input by the user
Manufacturing supply chain data analysis
My client has a web application which their partners must manually input the daily actual material stock into the application. My job was made a quantitative data analysis report to answer several questions based on the data : 1. Which data was not input correctly? 2. Which partner was not periodically input the data? 3. find a model that made a prediction if the data input was true or full of manipulation? 4. Find partners that not operate material distribution with a legal procedure To answer these questions, here was what i did : 1. make integration and collect needed data from SQL Server database, and put it as a pandas dataframe 2. pick the right features to answer the questions 3. Did several statistic and machine learning works using pandas & scikit-learn 4. Make a report in PDF 5. Client Presentation For the result, my client successfully update their application design, that improve the quality of the data that input by the user
Manufacturing supply chain data analysis
My client has a web application which their partners must manually input the daily actual material stock into the application. My job was made a quantitative data analysis report to answer several questions based on the data : 1. Which data was not input correctly? 2. Which partner was not periodically input the data? 3. find a model that made a prediction if the data input was true or full of manipulation? 4. Find partners that not operate material distribution with a legal procedure To answer these questions, here was what i did : 1. make integration and collect needed data from SQL Server database, and put it as a pandas dataframe 2. pick the right features to answer the questions 3. Did several statistic and machine learning works using pandas & scikit-learn 4. Make a report in PDF 5. Client Presentation For the result, my client successfully update their application design, that improve the quality of the data that input by the user
Manufacturing supply chain data analysis
4132887
My client has a time attendance system where got data from finger print / access control devices. The problem is, some users indicated came to the office in the midnite almost everyday, absolutely this situation is never happen. My job was to find out what happen occured, based on the 1 Million rows time clock data that generated by the system. Using pandas, i was enable to analyze the data, looking the trends, and finally conclude the anomaly. With the conclusion, the data anomaly always occurred when the finger print device failed to sync the data to the server.
Time attendance data anomaly analysis
4132891
My client has a web application which their partners must manually input the daily actual material stock into the application. My job was made a quantitative data analysis report to answer several questions based on the data : 1. Which data was not input correctly? 2. Which partner was not periodically input the data? 3. find a model that made a prediction if the data input was true or full of manipulation? 4. Find partners that not operate material distribution with a legal procedure To answer these questions, here was what i did : 1. make integration and collect needed data from SQL Server database, and put it as a pandas dataframe 2. pick the right features to answer the questions 3. Did several statistic and machine learning works using pandas & scikit-learn 4. Make a report in PDF 5. Client Presentation For the result, my client successfully update their application design, that improve the quality of the data that input by the user
Manufacturing supply chain data analysis
My client has a web application which their partners must manually input the daily actual material stock into the application. My job was made a quantitative data analysis report to answer several questions based on the data : 1. Which data was not input correctly? 2. Which partner was not periodically input the data? 3. find a model that made a prediction if the data input was true or full of manipulation? 4. Find partners that not operate material distribution with a legal procedure To answer these questions, here was what i did : 1. make integration and collect needed data from SQL Server database, and put it as a pandas dataframe 2. pick the right features to answer the questions 3. Did several statistic and machine learning works using pandas & scikit-learn 4. Make a report in PDF 5. Client Presentation For the result, my client successfully update their application design, that improve the quality of the data that input by the user
Manufacturing supply chain data analysis
My client has a web application which their partners must manually input the daily actual material stock into the application. My job was made a quantitative data analysis report to answer several questions based on the data : 1. Which data was not input correctly? 2. Which partner was not periodically input the data? 3. find a model that made a prediction if the data input was true or full of manipulation? 4. Find partners that not operate material distribution with a legal procedure To answer these questions, here was what i did : 1. make integration and collect needed data from SQL Server database, and put it as a pandas dataframe 2. pick the right features to answer the questions 3. Did several statistic and machine learning works using pandas & scikit-learn 4. Make a report in PDF 5. Client Presentation For the result, my client successfully update their application design, that improve the quality of the data that input by the user
Manufacturing supply chain data analysis
4132887
My client has a time attendance system where got data from finger print / access control devices. The problem is, some users indicated came to the office in the midnite almost everyday, absolutely this situation is never happen. My job was to find out what happen occured, based on the 1 Million rows time clock data that generated by the system. Using pandas, i was enable to analyze the data, looking the trends, and finally conclude the anomaly. With the conclusion, the data anomaly always occurred when the finger print device failed to sync the data to the server.
Time attendance data anomaly analysis

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