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Machine Learning and Data Science

$20/hr Starting at $25

  • Machine Learning: Proficient in developing and implementing machine learning models using Python libraries such as scikit-learn, pandas, and TensorFlow. Experienced in working with diverse types of data, including structured and unstructured data and large and complex datasets. Skilled in using machine learning techniques, including classification, clustering, regression, and recommendation systems, to solve business problems and improve operations.
  • Advanced Statistics: Experienced in using statistical techniques, including hypothesis testing, regression analysis, and time-series analysis, to analyze data and make predictions. Skilled in using R and Matlab to perform statistical analysis and data visualization.
  • SQL Skills: Proficient in using SQL to query and analyze data in relational databases. Skilled in using SQL to write complex queries, manipulate data, and join multiple tables. Able to work with large datasets efficiently and effectively.
  • Deep learning: Familiar with concepts related to deep learning, such as neural networks, convolutional neural networks, and recurrent neural networks. Skilled in using deep learning frameworks, such as TensorFlow, Keras, and PyTorch, to train and deploy custom models for image classification, speech recognition, and natural language processing tasks.
  • Natural Language Processing (NLP): Proficient in using NLP techniques, such as text classification, sentiment analysis, and named entity recognition, to extract insights from text data. Experienced in using NLP frameworks, such as spaCy, NLTK, and TextBlob. 

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$20/hr Ongoing

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  • Machine Learning: Proficient in developing and implementing machine learning models using Python libraries such as scikit-learn, pandas, and TensorFlow. Experienced in working with diverse types of data, including structured and unstructured data and large and complex datasets. Skilled in using machine learning techniques, including classification, clustering, regression, and recommendation systems, to solve business problems and improve operations.
  • Advanced Statistics: Experienced in using statistical techniques, including hypothesis testing, regression analysis, and time-series analysis, to analyze data and make predictions. Skilled in using R and Matlab to perform statistical analysis and data visualization.
  • SQL Skills: Proficient in using SQL to query and analyze data in relational databases. Skilled in using SQL to write complex queries, manipulate data, and join multiple tables. Able to work with large datasets efficiently and effectively.
  • Deep learning: Familiar with concepts related to deep learning, such as neural networks, convolutional neural networks, and recurrent neural networks. Skilled in using deep learning frameworks, such as TensorFlow, Keras, and PyTorch, to train and deploy custom models for image classification, speech recognition, and natural language processing tasks.
  • Natural Language Processing (NLP): Proficient in using NLP techniques, such as text classification, sentiment analysis, and named entity recognition, to extract insights from text data. Experienced in using NLP frameworks, such as spaCy, NLTK, and TextBlob. 

Skills & Expertise

AlgorithmsAnalyticsData AnalysisData ModelingData VisualizationMachine LearningMathematicsPower BIPython

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