The Monthly Wrap

The Internet of things is the new and vast field of opportunities in today’s era. In this digital world the most important thing is data and this is the only platform every one need to work. Without this, nothing would be possible in digital world. As the use of technology and its advancement increase the quantity of data automatically. According to the predictions of data scientists tremendous amount of data will be increased in near future. To maintain and extract the important information from this data automation of these processes is required. According to various agencies like data fabric trends report, by the end of 2025 data automation market will be reached to $4.2 billion. So Iot is the one area for data collection and its automation. In the upcoming future working and job opportunities in this field is the hottest platform for the youth.  Figure 1: IoT Infrastructure and Technologies IoT platform provide the various services for the ease of life, business improvement, refine

  Machine Learning (ML) Machine learning is a branch of AI, used to process and analyse the data using various algorithms that mimics the learning behaviour of humans for analysing the data. These algorithms predict the outcomes without intervention of human. It provides the systems that automatically learn and improve based on their experience.  Fig 1 depicts the process of machine learning. It consists of five steps starting with collection of data and ends at model deployment. These are 5 basic steps: Collection of Data from various data source Data cleaning and Feature Engineering Model building and Selection of ML Algorithm Model Evaluation Model Deployment Fig. 1 Basic Process of Machine Learning Generally, Data collection is the key process in ML. Based on the addressed problem, we have to obtain the data from different sources. Data can be collected from social media, public opinion poll, or survey of the product success or failure.  Next step in ML is data cleaning.  Before st

  DATA SCIENCE AND APACHE SPARK Data Science has transformed the world. It has contributed towards the excessive growth of data and to develop intelligent systems. To analyze large amounts of data, various Data Science tools are available to Data Scientists. Among several available tools, Apache Spark has revolutionized the Data Science industry in a great manner. Apache Spark Spark is one of the open-source which is capable to process huge amount of data efficiently with very high speed. Due to its data streaming capability, Spark has left behind the other existing Big Data platforms. It also carry out machine learning operations and SQL workloads that allow us to access the datasets. Spark is developed on application levels through multiple languages like Python, Java, R, and Scala. Components of Apache Spark for Data Science Main components of Spark are – Spark Core, Spark SQL, Spark Streaming, Spark MLlib, Spark R and Spark GraphX. SNo Components Description 1 Spark Core This is th