Keywords
Machine Learning
Artificial Intelligence
Data Analysis
Data Modeling
Data Visualization
Python (Programming Language)
Matplotlib
Programming Languages
Java (Programming Language)
Algorithms
Artificial Neural Networks
Automation
Unit Testing
C++ (Programming Language)
Cluster Analysis
Software Quality
Continuous Integration
Data Structures
MATLAB
Natural Language Processing
Named Entity Recognition
NLTK (NLP Analysis)
NumPy
Predictive Modelling
Tensorflow
Sentiment Analysis
Tableau (Software)
Deep Learning
Keras
Pandas
Scikit Learn
Technical Acumen
Spacy
Recurrent Neural Networks
Unsupervised Learning
+ 25 more keywords
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Skills
As an AI Engineer/Machine Learning Engineer, I possess a wide range of technical skills in various AI technologies, programming languages, and data modeling. I am proficient in neural networks, including ANN, CNN, and RNN, and have experience in both supervised and unsupervised learning. I am skilled in Pytorch, TensorFlow, and Keras, and have developed and implemented models for various applications. I am also experienced in Lstm and Gru models, which are specialized types of recurrent neural networks.
Additionally, I am skilled in using Python libraries, such as Matplotlib, Numpy, Pandas, and SciKit Learn, for data analysis, data visualization, and machine learning tasks. I have strong knowledge of data structures and algorithms, which are crucial for developing efficient machine learning models. I am experienced in predictive modeling, including regression, classification, and clustering, and proficient in using various statistical and machine learning techniques.
I also have experience in natural language processing, including sentiment analysis, text classification, and named entity recognition. I am skilled in using NLP libraries such as NLTK, Spacy, and Gensim. Furthermore, I am proficient in using visualization tools, such as Matplotlib, Seaborn, and Tableau, for exploratory data analysis and presenting findings.
My skills in C++(STL), PySpark.ML, Python, and Java enable me to implement efficient and scalable machine learning models for various applications. I am also knowledgeable in unit testing and CI/CD tools, which ensure code quality and automate the development process. Overall, my skills and experience in AI technologies, programming languages, and data modeling enable me to design, develop, and deploy effective machine learning models for various applications.
Project history
Design and implement algorithms: Design and implement algorithms for signal processing, data analysis, and navigation calculations.
Code development: Responsible for coding, testing, and debugging the software using MATLAB, C, and C++ programming languages.
Integration and testing: Integrate your software with hardware components, perform system testing, and troubleshoot any issues that arise.
Documentation: Responsible for documenting my code and creating user manuals and technical reports for your project.
Collaboration: Collaboratively with other developers, project managers, and stakeholders, sharing ideas and contributing to advancing the project goals.
Keep up-to-date with developments in the field: Stay current with new technologies and best practices in signal processing, navigation, and software development using MATLAB, C, and C++.
Design machine learning models: I had responsible for designing machine learning models to meet the project goals. This may involve researching and selecting the appropriate model architecture, collecting and preparing high-quality data, and setting up machine learning pipelines.
Analyze results: analyze the results of the machine learning and evaluate the performance of my model. This may involve performing statistical tests, comparing the performance of different models, and writing detailed reports on the results.
Optimize models: I adjust my model's hyperparameters to improve its performance, as well as finding ways to reduce training times or improve model efficiency.
Write articles: responsible for writing research papers to present my results and share them with the scientific community. This may include writing abstracts, publications, and presentations for conferences.
Collaborate with other researchers: I collaboratively with other AI researchers on joint research projects, sharing ideas, discussing results, and contributing to advancing knowledge in the field.
Stay up-to-date with developments in the field: I follow trends and developments in the field of artificial intelligence, reading research papers, attending conferences, and discussing with other researchers. I also need to use your expertise to provide recommendations to the project team on emerging technologies and best practices in AI.
- Developing and maintaining applications using Python and Java programming languages.
- Interacting with clients to understand their requirements and design software solutions that met their needs.
- Writing efficient and maintainable code, and testing applications to ensure they met quality standards.
- Implementing data storage and management solutions using SQL.
- Collaborating with cross-functional teams to deliver high-quality software solutions in an Agile environment.