Innovative Machine Learning Engineer and Natural Language Processing skilled with around 2 years of experience in machine learning model design, development, testing, and deployment. Good experienced in delivering end-to…
Innovative Machine Learning Engineer and Natural Language Processing skilled with around 2 years of experience in machine learning model design, development, testing, and deployment. Good experienced in delivering end-to-end machine learning and data science projects with the right choice of technologies, and algorithms to solve real-world use cases in the retail industry.
• Performed large-scale data analysis and developed effective statistical models through
various regression and classification algorithms-Linear Regression, Logistic Regression,
Decision tree, Random Forest.
• Research and implement appropriate ML algorithms and tools, select appropriate datasets
and perform statistical analysis.
• Strong coding ability both in producing clean and efficient code and understanding large code
bases.
• Extensive hands-on experience and high proficiency with structured, semi-structured, and
unstructured data, using broad range of data science programming languages like Python,
SQL.
• Skilled in using pandas, Numpy, Seaborn, Matplotlib, Scikit-Learn, and NLTK in Python for
developing various machine-learning algorithms.
Performed large-scale data analysis and developed effective statistical models through various regression and classification algorithms-Linear Regression, Logistic Regression, Decision tree, Random Forest.
Research and implement appropriate ML algorithms and tools, select appropriate datasets and perform statistical analysis.
Strong coding ability both in producing clean and efficient code and understanding large code bases.
Extensive hands-on experience and high proficiency with structured, semi-structured, and unstructured data, using broad range of data science programming languages like Python, SQL.
Skilled in using pandas, Numpy, Seaborn, Matplotlib, Scikit-Learn, and NLTK in Python for developing various machine-learning algorithms.
Data to extract insights and make data-driven decisions.
Gain experience in model development and evaluation.
Present findings and insights to non-technical stakeholders within the organization.
Experience on data analysis and visualization to machine learning model development and evaluation.
Collect, clean, preprocess, and analyze data includes working with datasets, performing data wrangling, and conducting exploratory data analysis (EDA).
Write code to manipulate data, create visualizations
Effectively communicate and insights, both in written reports and through presentations.
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