Skip to content

Details

*** Event details ***
*** This event is an in-person event happening at Chennai location.
*** This event is having a hands-on workshop and participants are expected to bring their laptops & chargers
*** Request you to read the details completely before join the event.
*** If your meetup RSVP status is "going", then you are confirmed for this meetup.

*** Registration for this event is closed ***

*** Event Plan ***
02-Jul-2024 : Agenda finalisation & Speaker announcement
12-Jul-2024 : Event registration ends
11-Jul-2024 : Attendees confirmation
13-Jul-2024 : In-person event
*** Agenda ***
0930 AM to 1000 AM - Registration, community introduction.
1000 AM to 1100 AM - Getting started with Gemini on Vertex AI by Navaneethan Gopal.
1100 AM to 11:20 AM - Tea break
1120 AM to 0100 PM - Deep learning 101 (on CNN) workshop-part 1 by Karthikeyan VK
0100 PM to 0140 PM - Lunch & Networking
0140 PM to 0420 PM - Deep learning 101 (on CNN) workshop-part 2 by Karthikeyan VK
0420 PM to 0430 PM - Feedback & event closure

*** About speakers ***
Karthikeyan VK - CTO, PROIndia, M.Tech in Data Science & Engineering | Author - Karthik is from strong background in software architecture, with particular expertise in designing SAAS products using micro-services and serverless technologies. Proficient in developing and integrating large, distributed machine learning system lifecycle utilizing cutting-edge open-source technologies. Demonstrated proficiency in using PyTorch, TensorFlow, and Keras for training and deploying machine learning models.

Extensive startup experience, with a track record of building multiple startups from ground zero. Skilled at assembling and leading a Web/Mobile development team from the ground up, consistently delivering successful projects. A seasoned product builder, having designed and launched several innovative and profitable products, demonstrating a deep understanding of the complete product lifecycle.

Navaneethan Gopal - Data Science Manager @ Ingram Micro | AI CoE - MLOps - Navaneethan is working with business teams to understand the requirements and translate that into analytics solution. Handling projects for new leads, sales, marketing analytics, revenue enhancement through up-sell / cross sell and customer experience analytics. Strong interpersonal skills, experience in delivery of statistical analysis, people and client management, driving process efficiency and best practices.

*** About sessions ***
"Deep Learning 101: Hands-On Workshop on Image Classification." In this workshop, you will learn the fundamentals of deep learning and apply these concepts through a practical, hands-on approach to building a Convolutional Neural Network (CNN) for image classification.

### Workshop Outline:

  1. Introduction to Deep Learning
  • Overview of deep learning and its applications.
  • Introduction to neural networks.
  • Understanding the importance of image classification in deep learning.
  1. Understanding Convolutional Neural Networks (CNNs)
  • Structure of a CNN: Input Layer, Convolutional Layer, Pooling Layer, Fully Connected Layer, and Output Layer.
  • The role of each layer in feature extraction and classification.
  1. Setting Up the Environment
  • Introduction to the Jupyter notebook interface.
  • Required libraries: TensorFlow, Keras, NumPy, Pandas, Matplotlib, and Scikit-learn.
  1. Data Preparation
  • Downloading and preparing the dataset.
  • Loading and preprocessing images.
  • Splitting data into training and testing sets.
  1. Building the CNN Model
  • Defining the architecture of the CNN.
  • Adding convolutional, pooling, and fully connected layers.
  • Compiling the model with appropriate loss functions and optimizers.
  1. Training the Model
  • Setting training parameters.
  • Training the model on the dataset.
  • Monitoring the training process and evaluating performance.
  1. Evaluating the Model
  • Analyzing model accuracy and loss.
  • Visualizing training and validation performance.
  • Making predictions on new data.
  1. Hands-On Coding Session
  • Step-by-step guidance through the provided notebook.
  • Live coding to implement each part of the process.
  • Troubleshooting and debugging common issues.
  1. Q&A and Further Learning Resources
  • Open floor for questions and discussion.
  • Recommendations for further learning and advanced topics in deep learning.

### Prerequisites:

  • Basic knowledge of Python programming.
  • Familiarity with basic machine learning concepts is helpful but not required.
  • A laptop with internet access to download the necessary datasets and libraries.

*** Archive ***
Meetup #42

Related topics

Events in Chennai

You may also like