Deep Learning by TensorFlow 2.0 Basic to Advance with Python

🎓 Deep Learning by TensorFlow 2.0: Basic to Advanced with Python 🚀

Course Headline: Unlock the full potential of Artificial Intelligence and become a certified Deep Learning Professional by mastering TensorFlow 2.0 through our comprehensive, hands-on course designed by industry expert Shiv Onkar Deepak Kumar.

Course Description: In the ever-evolving landscape of AI, Deep Learning stands out as the cornerstone technology driving innovation across industries. With TensorFlow 2.0 being one of the most popular and versatile libraries for deep learning, our course is meticulously structured to guide you from the fundamentals to advanced applications in a practical, immersive manner.

📚 What You'll Learn:

• Hands-On Approach: Dive into 80% hands-on projects with 20% theoretical knowledge to ensure you can work on Deep Learning projects independently.
• TensorFlow 2.x Foundation: Understand the core concepts of TensorFlow and its ecosystem.
• Regression Models: Explore two state-of-the-art regression models to predict outcomes.
• Classification Models: Implement two advanced classification models to categorize data accurately.
• Image Classifications with CNNs: Learn to apply Convolutional Neural Networks (CNNs) through five different models, enhancing your image recognition skills.
• Data Augmentation: Master the use of Image Data Generator for robust image classification tasks.
• Sequence Data with RNNs: Utilize Recurrent Neural Networks (RNNs) to handle time-series data and sequence predictions effectively.
• Transfer Learning: Discover how to leverage pre-trained models to achieve higher accuracy with less training data.
• Generative Adversarial Networks (GANs): Dive into GANs to understand and create generative models that can generate new data samples.
• Hyperparameters Tuning: Optimize your models by fine-tuning key hyperparameters for maximum performance.
• Overfitting Prevention: Learn strategies to effectively prevent overfitting, a common challenge in Deep Learning.
• Best Practices and Award-winning Architectures: Gain insights into the industry's best practices and explore award-winning neural network architectures.

Why Choose This Course?

• Practical, Real-World Projects: Engage with projects that mimic real-world scenarios, giving you the confidence to tackle actual Deep Learning challenges.
• Comprehensive Curriculum: A blend of theoretical concepts and hands-on learning ensures a solid understanding of Deep Learning principles.
• Industry-Relevant Skills: Acquire skills that are in high demand across various sectors, including healthcare, finance, and autonomous driving technologies.
• Interactive Learning Experience: Benefit from interactive discussions, quizzes, and real-time feedback to reinforce your learning journey.

Who Is This Course For?

• Aspiring Data Scientists aiming to specialize in Deep Learning.
• Software Developers looking to expand their skillset with advanced AI techniques.
• Machine Learning Engineers seeking to improve their model performance and deployment strategies.
• Graduate students, researchers, and academicians interested in AI applications.

Enroll now and embark on a journey to master Deep Learning with TensorFlow 2.0. Take the first step towards becoming an expert in one of the most exciting fields of technology today! 🌟

Prerequisites:

• Basic knowledge of Python programming language.
• Understanding of Machine Learning fundamentals.
• Familiarity with the core concepts of neural networks.

Tools and Technologies Covered:

• TensorFlow 2.0
• Keras API for TensorFlow
• Jupyter Notebooks for project implementation
• Python Libraries (NumPy, Matplotlib, etc.)

Instructor Background: Shiv Onkar Deepak Kumar is a seasoned Deep Learning professional with extensive experience in applying AI to solve real-world problems. With a strong academic background and years of industry expertise, Shiv brings practical knowledge and insights that will elevate your understanding and application of deep learning techniques.