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Reading list

6 Steps of Machine learning Lifecycle Introduction to Predictive Modeling
Introduction to Exploratory Data Analysis & Data Insights Descriptive Statistics Inferential Statistics How to Understand Population Distributions?
Reading Data Files into Python Different Variable Datatypes
Probability for Data Science Basic Concepts of Probability Axioms of Probability Conditional Probability
Central Tendencies for Continuous Variables Spread of Data KDE plots for Continuous Variable Overview of Distribution for Continuous variables Normal Distribution Skewed Distribution Skeweness and Kurtosis Distribution for Continuous Variable
Central Tendencies for Categorical Variables Understanding Discrete Distributions Performing EDA on Categorical Variables
Dealing with Missing Values Understanding Outliers Identifying Outliers in Data Outlier Detection in Python Outliers Detection Using IQR, Z-score, LOF and DBSCAN
Sample and Population Central Limit Theorem Confidence Interval and Margin of Error
Bivariate Analysis Introduction
Covariance Pearson Correlation Spearman's Correlation & Kendall's Tau Correlation versus Causation Tabular and Graphical methods for Bivariate Analysis Performing Bivariate Analysis on Continuous-Continuous Variables
Tabular and Graphical methods for Continuous-Categorical Variables Introduction to Hypothesis Testing P-value Two sample Z-test T-test T-test vs Z-test Performing Bivariate Analysis on Continuous-Catagorical variables
Chi-Squares Test Bivariate Analysis on Categorical Categorical Variables
Multivariate Analysis A Comprehensive Guide to Data Exploration The Data Science behind IPL
Supervised Learning vs Unsupervised Learning Reinforcement Learning Generative and Descriminative Models Parametric and Non Parametric model
Machine Learning Pipeline Preparing Dataset Build a Benchmark Model: Regression Build a Benchmark Model: Classification
Evaluation Metrics for Machine Learning Everyone should know Confusion Matrix Accuracy Precision and Recall AUC-ROC Log Loss R2 and Adjusted R2
Dealing with Missing Values Replacing Missing Values Imputing Missing Values in Data Working with Categorical Variables Working with Outliers Preprocessing Data for Model Building
Understanding Cost Function Understanding Gradient Descent Math Behind Gradient Descent Assumptions of Linear Regression Implement Linear Regression from Scratch Train Linear Regression in Python Implementing Linear Regression in R Diagnosing Residual Plots in Linear Regression Models Generalized Linear Models Introduction to Logistic Regression Odds Ratio Implementing Logistic Regression from Scratch Introduction to Scikit-learn in Python Train Logistic Regression in python Multiclass using Logistic Regression How to use Multinomial and Ordinal Logistic Regression in R ? Challenges with Linear Regression Introduction to Regularisation Implementing Regularisation Ridge Regression Lasso Regression
Introduction to K Nearest Neighbours Determining the Right Value of K in KNN Implement KNN from Scratch Implement KNN in Python
Bias Variance Tradeoff Introduction to Overfitting and Underfitting Visualizing Overfitting and Underfitting Selecting the Right Model What is Validation? Hold-Out Validation Understanding K Fold Cross Validation
Introduction to Feature Selection Feature Selection Algorithms Missing Value Ratio Low Variance Filter High Correlation Filter Backward Feature Elimination Forward Feature Selection Implement Feature Selection in Python Implement Feature Selection in R
Introduction to Decision Tree Purity in Decision Tree Terminologies Related to Decision Tree How to Select Best Split Point in Decision Tree? Chi-Squares Information Gain Reduction in Variance Optimizing Performance of Decision Tree Train Decision Tree using Scikit Learn Pruning of Decision Trees
Introduction to Feature Engineering Feature Transformation Feature Scaling Feature Engineering Frequency Encoding Automated Feature Engineering: Feature Tools
Understanding how to solve Multiclass and Multilabled Classification Problem Evaluation Metrics: Multi Class Classification
Introduction to Ensemble Techniques Basic Ensemble Techniques Implementing Basic Ensemble Techniques Finding Optimal Weights of Ensemble Learner using Neural Network Why Ensemble Models Work well?
Introduction to Stacking Implementing Stacking Variants of Stacking Implementing Variants of Stacking Introduction to Blending Bootstrap Sampling Introduction to Random Sampling Hyper-parameters of Random Forest Implementing Random Forest Out-of-Bag (OOB) Score in the Random Forest IPL Team Win Prediction Project Using Machine Learning Introduction to Boosting Gradient Boosting Algorithm Math behind GBM Implementing GBM in python Regularized Greedy Forests Extreme Gradient Boosting Implementing XGBM in python Tuning Hyperparameters of XGBoost in Python Implement XGBM in R/H2O Adaptive Boosting Implementing Adaptive Boosing LightGBM Implementing LightGBM in Python Catboost Implementing Catboost in Python
Different Hyperparameter Tuning methods Implementing Different Hyperparameter Tuning methods GridsearchCV RandomizedsearchCV Bayesian Optimization for Hyperparameter Tuning Hyperopt
Understanding SVM Algorithm SVM Kernels In-depth Intuition and Practical Implementation SVM Kernel Tricks Kernels and Hyperparameters in SVM Implementing SVM from Scratch in Python and R
Introduction to Principal Component Analysis Steps to Perform Principal Compound Analysis Computation of Covariance Matrix Finding Eigenvectors and Eigenvalues Implementing PCA in python Visualizing PCA A Brief Introduction to Linear Discriminant Analysis Introduction to Factor Analysis
Introduction to Clustering Applications of Clustering Evaluation Metrics for Clustering Understanding K-Means Implementation of K-Means in Python Implementation of K-Means in R Choosing Right Value for K Profiling Market Segments using K-Means Clustering Hierarchical Clustering Implementation of Hierarchial Clustering DBSCAN Defining Similarity between clusters Build Better and Accurate Clusters with Gaussian Mixture Models
Understand Basics of Recommendation Engine with Case Study
8 Ways to Improve Accuracy of Machine Learning Models
Introduction to Dask Working with CuML
Introduction to Machine Learning Interpretability Framework and Interpretable Models model Agnostic Methods for Interpretability Implementing Interpretable Model Understanding SHAP Out-of-Core ML Introduction to Interpretable Machine Learning Models Model Agnostic Methods for Interpretability Game Theory & Shapley Values
Introduction to AutoML Implementation of MLBox Introduction to PyCaret TPOT Auto-Sklearn EvalML
Pickle and Joblib Introduction to Model Deployment
Deploying Machine Learning Model using Streamlit Deploying ML Models in Docker Deploy Using Streamlit Deploy on Heroku Deploy Using Netlify Introduction to Amazon Sagemaker Setting up Amazon SageMaker Using SageMaker Endpoint to Generate Inference Deploy on Microsoft Azure Cloud Introduction to Flask for Model Deploying ML model using Flask
Model Deployment in Android Model Deployment in Iphone

I Have Booked my Seat. Here’s How You can Register for NVIDIA AI Summit 2024.

Pankaj9786
Pankaj9786 12 Aug, 2024
7 min read

Introduction

After the successful wrap-up of the much-awaited Datahack Summit 2024, India will witness another big event: the NVIDIA AI Summit 2024. It is scheduled for October 23rd and 25th at the Jio World Conventional Centre in Mumbai, India. With the release of the notification, you might be wondering what to expect from this event.

At the AI Summit, you will witness how AI solves India’s grand challenges, developers build cutting-edge solutions for local and global markets, and industry leaders converge to share groundbreaking insights. This vision is set to become a reality at the NVIDIA AI Summit 2024, a landmark event that promises to redefine the landscape of artificial intelligence. One burning question emerges as we stand on the cusp of an AI revolution: How will you contribute to this transformative journey? The answer awaits you at the Jio World Convention Centre in Mumbai, where NVIDIA is poised to unlock the limitless potential of AI. Are you ready to be part of this game-changing conversation?

Overview

  1. The article introduces the highly anticipated NVIDIA AI Summit 2024, highlighting its significance and upcoming schedule in Mumbai.
  2. The summit promises to showcase AI solutions for India’s challenges, bringing together developers, industry leaders, and innovators.
  3. Attendees can expect diverse sessions on generative AI, edge computing, robotics, and AI policy tailored for various professional roles.
  4. The summit offers full-day, hands-on workshops to help participants deepen their technical skills and earn certifications.
  5. The article provides a step-by-step guide to registering for the summit, including pricing details and payment options.

Table of contents

Discover What’s Possible With AI

The NVIDIA AI Summit 2024 goes beyond a typical conference; it explores the future of AI. Attendees will gain valuable insights from industry leaders through over 50 sessions and live demonstrations, covering areas like generative AI, large language models (LLMs), industrial digitalization, supercomputing, and robotics. Notably, 70% of the use cases presented will focus on solving India’s grand challenges, underscoring the country’s pivotal role in the global AI landscape.

The summit serves as a platform for developers, researchers, business leaders, and policymakers to come together and explore AI’s transformative potential. With the aim of building solutions for India and the world, the event is designed to foster collaboration, spark innovation, and drive progress in AI technologies.

John Snyder, Senior Data Scientist, ThreatConnect, Said:

NVIDIA workshops help me stay at the cutting edge of my field. With highly motivated students and very knowledgeable instructors, the experience is as enjoyable as it is informative. The consistently relevant examples will keep me coming back for years!

Explore Sessions for the Work You Do

The NVIDIA AI Summit 2024 offers diverse sessions tailored to the unique needs of different professional roles. Whether you’re a developer, researcher, CXO, startup founder, or venture capitalist, there’s something for everyone. Here’s a glimpse of what you can expect:

  • Generative AI and LLMs: Gain practical insights into the power of generative AI from leading policymakers, researchers, and business leaders. This track will explore best practices and innovative applications of LLMs across various industries.
  • Cybersecurity and Edge Computing: This track will explore how AI revolutionizes edge computing solutions in retail, manufacturing, healthcare, and smart cities. It will highlight the critical role of AI in enhancing security and efficiency at the edge.
  • Robotics and Edge Computing: This track will explore the future of robotics in the manufacturing and healthcare industries. It will dive into end-to-end solutions for developing, simulating, and deploying robots powered by generative physical AI.
  • Industrial Digitalization and Data Center/Cloud: Learn the latest insights and best practices for building scalable AI infrastructure. This track will focus on the intersection of AI, data centers, and cloud computing, offering strategies for optimizing performance and efficiency.
  • AI Policy and Business Strategy: Transform your business into an AI-driven organization with NVIDIA’s advanced platform. This track will cover the full innovation stack, from accelerated infrastructure to enterprise-grade software and AI models, offering a roadmap for businesses leveraging AI.

Fireside Chat With Jensen Huang

One of the most anticipated sessions of the summit is the Fireside Chat with NVIDIA’s founder and CEO, Jensen Huang, scheduled for October 24. This intimate conversation will provide attendees with a rare opportunity to hear directly from one of the leading visionaries in AI.

Huang’s insights into the future of AI, the challenges and opportunities ahead, and NVIDIA’s role in shaping the AI ecosystem will provide invaluable information for anyone invested in the future of technology.

If you are looking for a GenAI course online, then – Explore GenAI Pinnacle Program today!

Hands-On Workshops and Training Sessions

The NVIDIA AI Summit 2024 offers a series of full-day, hands-on workshops for those looking to deepen their technical expertise. These sessions are designed to go beyond the basics, providing in-depth training led by subject matter experts. Attendees will be able to earn technical certifications and gain practical experience with next-generation NVIDIA technology and tools.

  • Fundamentals of Deep Learning: Engage in hands-on exercises in computer vision and natural language processing, mastering the key techniques required to train deep learning models.
  • Rapid Application Development With Large Language Models (LLMs): Learn how to harness the power of LLMs to automate language-related tasks, streamline operations, and increase productivity.
  • Introduction to Transformer-Based Natural Language Processing: Start using Transformer-based models for text classification and named-entity recognition (NER) tasks.
  • Efficient Large Language Model (LLM) Customization: Explore techniques to efficiently customize pretrained LLMs for specific use cases using NVIDIA NeMo™ service.
  • Fundamentals of Accelerated Data Science: Gain insights into building scalable, efficient data science pipelines using the right balance of CPUs, DRAMs, disk memory, and GPUs.

These workshops are an excellent opportunity for professionals to stay ahead of the curve and gain the skills needed to thrive in an AI-driven world.

Hyunkoo Kwak, Learning and Development Lead, Manufacturing Technology Center, Samsung Electronics, Said:

NVIDIA set up a great virtual training environment, and we were taught directly by deep learning/CUDA experts. This enabled our team to understand the concepts and how to use the codes in the hands-on lab, which helped us understand the subject matter more deeply. The team enjoyed the class immensely.

How to Register for NVIDIA AI Summit?

Here’s how you can register for NVIDIA AI Summit:

  1. Search for NVIDIA AI Summit on Google Search

    Open your preferred browser and type “NVIDIA AI Summit” into the Google search bar. Look for the official summit page in the search results and click on the link to access the event website.NVIDIA AI SUMMIT

  2. On the Website, Look for the Register Now

    Once you’re on the NVIDIA AI Summit website, browse through the homepage or the event details section to locate the “Register Now” button. This is usually prominently displayed to guide users through the registration process.NVIDIA AI SUMMIT

  3. After that, Login or Create Your Account

    After clicking “Register Now,” you can log in with your existing account. If you don’t have an account, you can create a new one by providing basic information such as your name, email, and password.NVIDIA AI SUMMIT

  4. Verify Your Email and Submit Once Done

    After you create an account, check your inbox for a verification email, open it, click the link to verify your email address, and then return to the registration process to continue.
    NVIDIA AI SUMMIT

  5. Now, You Will be Redirected to the Registration Page; fill in all the Details

    After verifying your email, you’ll be redirected to the registration page. Here, you must provide detailed information, including your name, contact information, organization, and other required details relevant to the summit.NVIDIA AI SUMMIT

  6. After Registration – Make the Payment

    You’ll be directed to the payment page once you’ve filled in all the necessary details. Choose your preferred payment method, enter your payment information, and complete the transaction to secure your spot at the NVIDIA AI Summit.NVIDIA AI SUMMIT

Pricing of NVIDIA AI Summit 2024 Ticket

Here’s the pricing of NVIDIA AI Summit 2024:

The NVIDIA AI Summit 2024 offers several registration packages to suit different needs:

  • Conference Pass: Connect with industry leaders, developers, and business strategists. Early-bird pricing is available until September 11, with a 50% discount, bringing the price to 4,000 INR (plus applicable taxes).
  • Exhibits Only Pass: Gain insights from over 30 exhibitors at the showcase. Early-bird pricing is 3,000 INR (plus applicable taxes).
  • Full-Day Workshops: Attend hands-on technical workshops for 10,000 INR per person. Group discounts are available, reducing the price to 8,000 INR per person (plus applicable taxes) for groups of three or more.

With limited quantities available, it’s essential to register early to secure your spot at this highly anticipated event.

Conclusion

The NVIDIA AI Summit 2024 opens the door to the future of AI. Explore the latest technological advancements, gain practical insights, and connect with industry leaders—this summit has something for everyone. Attend to gain knowledge and join a global conversation shaping the future of AI.

Seize this opportunity to lead in AI innovation. Register now to secure your place at the NVIDIA AI Summit 2024 and discover what’s possible as we push the boundaries of technology together.

Frequently Asked Questions

Q1. What is the purpose of the AI Summit?

Ans. The AI Summit brings together industry leaders, innovators, researchers, and practitioners to explore the latest advancements, trends, and applications in artificial intelligence. It serves as a platform for networking, knowledge sharing, and collaboration in the AI community.

Q2. Who should attend the AI Summit?

Ans. The AI Summit is ideal for professionals across various sectors, including data scientists, AI researchers, machine learning engineers, tech entrepreneurs, business leaders, and anyone interested in understanding and leveraging AI technologies. It’s also beneficial for those looking to stay updated on AI trends and innovations.

Q3. What topics are typically covered at the AI Summit?

Ans. Topics usually include AI ethics, machine learning, deep learning, natural language processing, AI in healthcare, autonomous systems, AI-driven innovation in industries like finance and retail, and the future of AI. Discussions on regulatory issues, AI’s impact on society, and emerging technologies are also common.

Q4. What networking opportunities are available at the AI Summit?

Ans. The AI Summit offers various networking opportunities, including panel discussions, workshops, breakout sessions, and social events. Attendees can connect with industry leaders, explore potential partnerships, and discuss AI-related challenges and solutions in a collaborative environment. Some summits also offer one-on-one meetings and networking lounges.

AI summitArtificial Intelligencedata science conferencesdeep learningmachine learningNVIDIANVIDIA AI
Pankaj9786
Pankaj9786 12 Aug, 2024

Hi, I am Pankaj Singh Negi - Senior Content Editor | Passionate about storytelling and crafting compelling narratives that transform ideas into impactful content. I love reading about technology revolutionizing our lifestyle.

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