zekeLabs Blog


The Machine Learning Pipeline - Essential things to know before getting started with machine learning

The Machine Learning Pipeline - Essential things to know before getting started with machine learning    Awantik Das

Starting from development to deployment of machine learning, the journey of a product can be broken down to 7 important stages: Business Understanding, Data Wrangling, Visualization, Preprocessing, Model Training, Model Validation, Deployment




Big Data Processing with Deep Learning - Spark vs TensorFlow

Big Data Processing with Deep Learning - Spark vs TensorFlow    Awantik Das

  More and more organizations are integrating big data pipeline with deep learning infrastructure. This is something, Spark & TensorFlow folks have in mind as well. Let’s have a quick glance about their journey so far.   




What is future prospects of being a Django developer in India?

What is future prospects of being a Django developer in India?    Nalinee Choudhary

Apart from Training Django, due to increasing corporate requirement I am given assignments to interview candidates for Python & Django. Sharing my understanding of entire scenario from candidates prospective or corporate .




What are Big Data, Hadoop & Spark ? What is the relationship among them ?

What are Big Data, Hadoop & Spark ? What is the relationship among them ?    Awantik Das

Big Data is a problem statement & what it means is the size of data under process has grown to 100's of petabytes ( 1 PB = 1000TB ). Yahoo mail generates some 40-50 PB of data every day. Yahoo has to read that 40-50 PB of data & filter out spans. E-commerce...




Top 3 Applications of Apache Spark

Top 3 Applications of Apache Spark    Awantik Das

Distributed computation got with induction of Apache Spark in Big Data Space. Lightning performance, ease of integration, abstraction of inner complexity & programmable using Python, Scala, Java & R makes it one of the . Here we are discussing most widely ...




Is it still necessary to understand map-reduce paradigms for machine learning on large data sets?

Is it still necessary to understand map-reduce paradigms for machine learning on large data sets?    Awantik Das

Spark has covered a lot of mileage in a couple of years. And, with of Spark 2.0 - the internal implementation & optimization is abstracted the best possible way.




When Python has ML libraries, why do you need Apache Spark for analytics?

When Python has ML libraries, why do you need Apache Spark for analytics?    Awantik Das

Python provides various machine learning libraries such as sci-kit learn, Pylearn2, Theano, Pyevolve, Tensorflow etc. Apache Spark for analytics is now being widely adopted for machine learning. Following are the areas where Apache Spark gets hand with re...