Hi, I am a Data Scientist with 6+ years of experience in Data mining, Machine Learning, Deep learning, Statistical Modelling, Computer Vision and Natural Language Processing.
I have worked across various domains such as Banking, Stocks, Healthcare, Telecom, Energy and Business Development within last 5 years. I am a specialized Data Scientist and Machine Learning/Deep Learning Practitioner with a Preferred badge with over 100+ satisfied Clients.
Highlights:
▮ High-performing Data Science and Machine Learning professional with extensive experience in BI/ Data-Science/Machine Learning Deep Learning life cycle management from conception to completion.
▮ Having deep understanding of algorithms and data structure i.e. all facets of supervised and unsupervised learning and data munging techniques to meet the analytics and AI needs.
▮ Hands on with web scraping, database management, modelling, integrating disparate systems for data analysis or Machine Learning / Deep Learning/ AI applications.
▮ Deep Learning and Computer Vision, Big Data based high-performance based solutions and services.
- Highly proficient in Python.
- Experienced in building end-to-end pipelines for data manipulation, modelling, model deployment and optimizations.
- Knowledge of a variety of data visualization
- Knowledge of a variety of machine-learning algorithms:
- Regression (Linear, Logistic Regression, Multiple, GLM)
- Statistical Modelling (Cluster Analysis, Decision Trees, Regression)
- Classification (Naive Bayes, Support Vector Machine, Decision trees, Ensembles - Random forests, Gradient Boosting)
- K Means/ hierarchical/DBSCAN/Affinity/Agglomerative)
DeepNets/Theano/Keras/Tensorflow/CNN/LSTM/ImageProcessing/StockPrediction/Predictive Modelling/Pytorch/Theano.
- HoltWinters, ARIMA
- Tools (Tableau, PowerBI)
- Database Management System- MySQL, MongoDB, Teradata SQL, Hadoop, Cassandra
horrible response time and not honest, He didn't complete the work, leaved me in a very bad situation ,as i was counting on him, the project time line ends and he took about half the budget but didn't achieved 20% from the project.
Ultimately, data analysis is about understanding relationships among variables. Exploring data with multiple variables requires new, more complex tools, but enables a richer set of comparisons. In this course, you will learn how to describe relationships between two numerical quantities. You will characterize these relationships graphically, in the form of summary statistics, and through simple linear regression models.
2017
Certificaciones
P
Preferred Freelancer Program SLA
US English
Verificaciones
A tiempo
62 %
Dentro del presupuesto
62 %
Aceptar tarifa
81 %
Tasa de recontratación
14 %
¡Invitación enviada correctamente!
¡Gracias! Te hemos enviado un enlace para reclamar tu crédito gratuito.
Algo salió mal al enviar tu correo electrónico. Por favor, intenta de nuevo.