Each project comes with 2-5 hours of micro-videos explaining the solution.
Get access to 50+ solved projects with iPython notebooks and datasets.
Add project experience to your Linkedin/Github profiles.
I have worked for more than 15 years in Java and J2EE and have recently developed an interest in Big Data technologies and Machine learning due to a big need at my workspace. I was referred here by a... Read More
I have extensive experience in data management and data processing. Over the past few years I saw the data management technology transition into the Big Data ecosystem and I needed to follow suit. I... Read More
Ensemble methods are learning algorithms that construct a set of classifiers and then classify new data points by taking a vote of their predictions. The original ensemble method is Bayesian averaging, but more recent algorithms include error-correcting output coding, Bagging, and boosting. In the age of artificial intelligence and machine learning the ensemble, methods are becoming new norms, as a stand-alone model won't be sufficient to capture the dynamics of the data variability.
In this data science project, you will work with German credit dataset using classification techniques like Decision Tree, Neural Networks etc to classify loan applications using R.
In this machine learning project, we will use hundreds of anonymized features to predict if customers are satisfied or dissatisfied for one of the biggest banks - Santander
In this machine learning project, you will develop a machine learning model to accurately forecast inventory demand based on historical sales data.