An optimist, extrovert, & had a demonstrated history of delivering large & complex projects. Experienced in multiple
technologies like Machine learning, Deep learning, Ethical Hacking, Cloud, Data Science, DevOps, & Data Science.
Specialized in Big Data, Machine Learning, & Data Science!
Note: Each & every blog mentioned in my Portfolio
has been explained in complete depth using real world examples, & also they are explained in as much simplest
way as possible! My vision is to provide the right, accurate & complete knowledge which enables the in depth thought
process, which leads to the new creation!
Published 2 articles in the field of Machine Learning explaining Agglomerative Clustering which is type of Hierarchical Clustering, & DBSCAN algorithm which is part of Density based algorithm! Also, I published one article in the field pf networking explaining server!
Very important machine learning classification & regression algorithm, it acts as a base algorithm for ensemble machine learning algorithms! It falls under the category of bagging ensemble machinr learning! For complete blog click on the link given below!
For any of the algorithm in machin learning, or any model of Deep Learning, optimal weights for them are calculated by Gradient Descent only! This is the algorithm which makes model creation possible!
It is a technique which is used to find out the Time Complexity of any algorithm, if its reccurence relation is given!
It is subpart of clustering which is in turn part of unsupervised machine learning, and helps in finding patterns between the data without any given labels!
It is the most popular approach used in hierarchical clustering which is a type of unsupervised machine learning!
Ever wondered, what is the differnece between server & a computer/laptop/node. Refer this blog, I have explained server from real life examples & in complete depth.
This article clearly explains that whether RDBMS softwares can handle Big Data (Future Technology) or not! If not then why not, what are the limitations!
This blog explains the sub type of machine learning which is clustering which falls under the category of unspervised machine learning!
It is a type of clustering approach for solving the problem of data science or to find patterns in the data science approach to obtain an insight which can be used for boosting the economy of the economy!
It is a basic theorem to find the posterior probability, or we can say to find the probability of an event given that multiple events had already occured! It is used Naïve Bayes Theorem of machine learning!
It is an algorithm which is used to classify the records into various categories. It can be used in classification & Natural Language Processing!
It is an advanced version of Gradient Descent, it is very efficient & fast when the dataset is huge.
This topic is related to DevOps & Automation world, it is a part of CI/CD Pipeline, which is used in constructing softwares or automation part.
Complete end-to-end Flow of Data Science Pipeline is explained with each & every part in depth!
+91 8285095900
harshit.dawar55@gmail.com
itistechnologyworld@gmail.com