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I offer Machine Learning services.
Creating models for pattern recognition in the Data Array - the process of recognizing patterns by using machine learning algorithm. Pattern recognition can be defined as the classification of data based on knowledge already gained or on statistical information extracted from patterns and/or their representation. One of the important aspects of the pattern recognition is its application potential.
Image Processing - the use of computer algorithms to perform image processing on digital images.
Video Processing - a particular case of signal processing, in particular image processing, which often employs video filters and where the input and output signals are video files or video streams.
Natural Language Processing - a subfield of linguistics, computer science, information engineering, and artificial intelligence concerned with the interactions between computers and human (natural) languages, in particular how to program computers to process and analyze large amounts of natural language data.
For deep learning and NLP following are the tools i am most equipped with:
- 1. Keras
- 2. Tensorflow
- 3. OpenCV
- 4. Pandas
- 5. Numpy
- 6. Seaborn
- 7. Matplotlib
- 8. sklearn.
Price and time depends on work. Let's have a friendly talk about your project.
Services for data collection, data processing, data cleaning, data analysis, work with databases, hidup.
Data analysis is a part of a larger process of deriving business intelligence. The process includes the following steps:
Defining Objectives: Any study must begin with a set of clearly defined business objectives. Much of the decisions made in the rest of the process depends on how clearly the objectives of the study have been stated.
Posing Questions: An attempt is made to ask a question in the problem domain. For example, do red sports cars get into accidents more often than others?
Data Collection: Data relevant to the question must be collected from the appropriate sources. In the example above, data might be collected from a variety of sources including: DMV or police accident reports, insurance claims and hospitalization details. When data is being collected using surverys, a questionnaire to be presented to the subjects is needed. The questions should be appropriately modeled for the statistical method being used.
Data Wrangling: Raw data may be collected in several different formats. The collected data must be cleaned and converted so that data analysis tools can import it. For our example, we may receive DMV accident reports as text files, insurance claims from a relational database and hospitalization details as an API. The data analyst must aggregate these different forms of data and convert it into a form suitable for the analysis tools.
Data Analysis: This is the step where the cleaned and aggregated data is imported into analysis tools. These tools allow you to explore the data, find patterns in it, and ask and answer what-if questions. This is the process by which sense is made of data gathered in research by proper application of statistical methods.
Drawing Conclusions and Making Predictions: This is the step where, after sufficient analysis, conclusions can drawn from the data and appropriate predictions can be made. These conclusions and predications may then be summarized in a report delivered to end-users.
I can help you with any kind of work with python and C++, Just come up with any task you want to automate and I will help you.
- Creating programs for Python, C ++.
- Bug fixing
- Blockchain creation
- Microblogging creation
- Web application development
I will also be happy to help with the development of non-standard devices.