DataHour sessions are an excellent opportunity for aspiring individuals looking to launch a career in the data-tech industry, including students and freshers. Current professionals seeking to transition into the data-tech domain or data science professionals seeking to enhance their career growth and development can also benefit from these sessions. In this blog post, we will introduce you to some of the upcoming DataHour sessions, including contrastive learning for image classification, feature engineering, POS tagging, document segmentation using Layout Parser, and many more. Each session is designed to provide you with insights into various data tech topics, techniques, and methods. Attendees will learn from experts in the field, gain practical knowledge, and get to ask questions to clear their doubts. So, let’s take a closer look at the upcoming DataHour sessions.
Who can Attend these DataHour Sessions?
In this DataHour, Ashok will explain how Contrastive Learning is used for performing image classification. The model is trained to maximize the similarity between the positive examples and minimize the similarity between the negative examples. By doing this, the model learns to capture the important features of the data that are common across different views and that are distinctive between different data points.
📅Date: 10th March 2023
⌚Time: 07:00 PM IST
🔗Registration Link: Register Now
Contrastive learning has recently shown promising results in various applications and is an active area of research in the machine learning community.
In this DataHour, we will explore various feature engineering techniques that should be used before and during the modeling stage to mine more relevant features from the data. We will discuss methods for handling missing data, scaling and normalization, and feature selection.
📅Date: 10th March 2023
⌚Time: 08:30 PM IST
🔗Registration Link: Register Now
Additionally, we will delve into the role of data distribution in model performance, including the impact of skewed distributions and outliers.
In this DataHour, Deepika will explain about POS Tagging and Hidden Markov Model. Part-of-speech tagging (POS), also known as grammatical tagging or word-category disambiguation, is the process of marking up a word in a text or corpus corresponding to a particular part of speech based on its definition and context.
📅Date: 11th March 2023
⌚Time: 01:00 PM IST
🔗Registration Link: Register Now
Hidden Markov Models are probabilistic models that allow us to predict a sequence of unknown variables from a set of observed variables.
In this DataHour, Sumeet will give you a practical walkthrough of document segmentation using Layout Parser. He will introduce techniques for handling searchable/scanned PDFs and their limitations, which would be a foundation for the next step in using LayoutParser.
📅Date: 11th March 2023
⌚Time: 03:00 PM IST
🔗Registration Link: Register Now
Theoretical discussion regarding data preprocessing pipeline and post-processing pipeline with seamless integration to any commercial/open source will be conducted, following which various issues regarding OCR service will be discussed, which would be handled by this approach.
In this webinar, Vikas will introduce ensemble methods and discuss some of the most popular techniques, such as bagging, boosting, and stacking. He will also explore the benefits and drawbacks of ensemble methods and how they can be applied in various real-world scenarios, such as classification, regression, and anomaly detection.
📅Date: 12th March 2023
⌚Time: 01:00 PM IST
🔗Registration Link: Register Now
By the end of this webinar, you will better understand ensemble methods and how they can be leveraged to enhance the performance of your machine-learning models.
Deep metric learning is a technique that focuses on determining the similarity or dissimilarity between data through the use of a distance metric. One approach to deep metric learning is the use of Siamese networks. Two common loss functions are used when training a Siamese network for deep metric learning: Contrastive Loss and Triplet Loss.
📅Date: 12th March 2023
⌚Time: 3:00 PM IST
🔗Registration Link: Register Now
In this DataHour session, we will learn about training a Siamese network using the Triplets loss function with the sample image dataset. Which can be further used to build a visual search engine, object reidentifications, and face verification tasks.
This upcoming webinar is the perfect opportunity to learn the most important concepts in SQL, including group by, joins, and aggregate functions. By the end of the session, attendees will have a solid grasp of the fundamentals of SQL and be able to tackle challenging Leetcode questions with proper practice successfully.
📅Date: 13th March 2023
⌚Time: 7:00 PM IST
🔗Registration Link: Register Now
You’ll learn to group data based on specific criteria, join tables using common keys, and apply various aggregate functions to analyze large datasets. This foundational knowledge is essential for anyone looking to build a career in data analytics, database management, or software development.
In this DataHour, we aim to provide participants with a high-level understanding of the most common analytics use cases in the insurance industry. Firstly, the speakers will start with a brief overview of the insurance industry – how it works, types of insurance, etc.
📅Date: 13th March 2023
⌚Time: 8:30 PM IST
🔗Registration Link: Register Now
The next part of the session will focus on diving deep into any one of the use cases covering different aspects like objective, scope, data used, solution methodology, and results discussion.
Don’t miss out on this opportunity to take your tech journey to the next level. Register for DataHour sessions today and discover a world of possibilities. Have questions? Reach out to the speaker during the session or email us at [email protected]. Missed a session? No problem; catch up with recordings on our YouTube channel and resources sent to your registered email. What are you waiting for? Reserve your spot now!
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If you’re having trouble enrolling or would like to conduct a session with us. Contact us at [email protected].