Snehan Kekre, Instructor

Snehan Kekre

Machine Learning Instructor

Coursera Project Network

snehankekre

Bio

Snehan Kekre is a Technical Product Manager at Snowflake working on the Streamlit open-source team. He develops and ships features that delight users, and helps maintain the library. In the past, he has worked for Streamlit (pre-acquisition) as a Developer Advocate heading their Documentation team, and has authored and taught over 40+ guided projects on machine learning and data science at Coursera. He has also worked as a skills consultant at Coursera, and as content strategist at Rhyme.com.

Courses - English

Analyze Box Office Data with Plotly and Python

Analyze Box Office Data with Seaborn and Python

AutoML for Computer Vision with Microsoft Custom Vision

Automatic Machine Learning with H2O AutoML and Python

Build Multilayer Perceptron Models with Keras

Build Random Forests in R with Azure ML Studio

Build a Data Science Web App with Streamlit and Python

Build a Deep Learning Based Image Classifier with R

Build a Machine Learning Web App with Streamlit and Python

Create Interactive Dashboards with Streamlit and Python

Data Visualization with Plotly Express

Deep Learning Inference with Azure ML Studio

Exploratory Data Analysis with Seaborn

Fine Tune BERT for Text Classification with TensorFlow

Generate Synthetic Images with DCGANs in Keras

Linear Regression with NumPy and Python

Logistic Regression with NumPy and Python

Machine Learning Pipelines with Azure ML Studio

Machine Learning with H2O Flow

Multiple Linear Regression with scikit-learn

Optimize TensorFlow Models For Deployment with TensorRT

Perform Sentiment Analysis with scikit-learn

Predict Employee Turnover with scikit-learn

Predict Sales Revenue with scikit-learn

Predictive Analytics for Business with H2O in R

Predictive Modelling with Azure Machine Learning Studio

Principal Component Analysis with NumPy

Statistical Data Visualization with Seaborn From UST

Support Vector Machines with scikit-learn

Transfer Learning for NLP with TensorFlow Hub