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GCP - Cloud Providers - Part 2

GCP - Introduction to Cloud Computing - Part 1

Distributed Ledger Technology (DLT) Series - (Part 1)

The State of Machine Intelligence - AI Landscape

Understand Your Machine Learning Data With Descriptive Statistics in Python

How to Develop a Character-Based Neural Language Model in Keras

Data wrangling Using R

3D Plane wire frame Graph

Apache Spark Tutorial (Part 2 - RDD)

Apache Spark Tutorial (Part 1 - Introduction & Architecture)

HBase

Note: This is created for hands-on. Detailed notes will be added soon… Apache HBase is one such system. It is an open source distributed...

NoSQL

To maintain varied schema is not possible with traditional database, where NoSql comes into picture. NoSQL Databases: Key-Value :...

Data Science

Skills for Data Scientist: Data scientist way of thinking: In early stages, when we have a problem, physicist or chemist understand the...

Essentials of Machine Learning Algorithms (with Python and R Codes) - Part 10

Gradient Boosting & AdaBoost GBM & AdaBoost are boosting algorithms used when we deal with plenty of data to make a prediction with high...

Essentials of Machine Learning Algorithms (with Python and R Codes) - Part 9

Dimensionality Reduction Algorithms In the last 4-5 years, there has been an exponential increase in data capturing at every possible...

Essentials of Machine Learning Algorithms (with Python and R Codes) - Part 8

Random Forest Random Forest is a trademark term for an ensemble of decision trees. In Random Forest, we’ve collection of decision trees...

Essentials of Machine Learning Algorithms (with Python and R Codes) - Part 7

K-Means It is a type of unsupervised algorithm which solves the clustering problem. Its procedure follows a simple and easy way to...

Essentials of Machine Learning Algorithms (with Python and R Codes) - Part 6

KNN (K- Nearest Neighbors) It can be used for both classification and regression problems. However, it is more widely used in...

Essentials of Machine Learning Algorithms (with Python and R Codes) - Part 5

Naive Bayes It is a classification technique based on Bayes’ theorem with an assumption of independence between predictors. In simple...

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