Description
Python & TensorFlow: Deep Dive into Machine Learning course. Welcome to our Python & TensorFlow for Machine Learning complete course. This intensive program is designed for both beginners eager to enter the world of data science and seasoned professionals looking to deepen their understanding of machine learning, deep learning, and the capabilities of TensorFlow. Starting with Python—the cornerstone of modern AI development—we’ll guide you through its essential features and libraries that make data manipulation and analysis easy. As we delve into machine learning, you’ll learn fundamental algorithms and techniques, seamlessly moving from supervised learning to unsupervised learning, paving the way for the magic of deep learning. With TensorFlow, one of the most dynamic and widely used deep learning frameworks, we will explore how to build complex neural network architectures, optimize models, and deploy AI-based solutions. We don’t just want you to learn – we want you to master. By the end of the course, you will not only understand the theories but also gain practical experience, ensuring you are industry ready. Whether you want to innovate in AI research or implement solutions in business settings, this comprehensive course promises a deep understanding and equips you with the tools and knowledge to harness the power of Python, machine learning, and TensorFlow. We are excited about this trip and hope to see you inside!
What you will learn in the Python & TensorFlow: Deep Dive into Machine Learning course
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Understand the principles of machine learning, deep learning and their applications
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Configure and navigate TensorFlow by understanding its architecture and APIs
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Mastered learning algorithms such as linear regression, SVMs and decision trees
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Dive into unsupervised techniques including clustering and PCA
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Understanding and building neural networks, including CNNs and RNNs, using TensorFlow
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Evaluation and optimization of ML models, dealing with overfitting and mastering hyperparameter tuning
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Deploying TensorFlow models in production environments
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Apply the skills in a practical image classification project
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Moving from Python basics to ML and advanced enhancements to TensorFlow applications
This course is suitable for people who
- Beginners in Data Science and Artificial Intelligence: People looking to start their journey in machine learning and deep learning.
- Python Developers: Programmers familiar with Python looking to expand their skills in AI and TensorFlow applications.
- Data Analysts and Statisticians: Professionals looking to transfer or incorporate machine learning techniques into their analytics workflow.
- Techies: Those who are curious about the latest AI trends and want to work with TensorFlow and Python.
- Students: Undergraduate or graduate students studying computer science, data science, or related fields who want a comprehensive and applied overview.
- Career changes: Professionals from other disciplines who want to move into data science or AI roles.
- Researchers: People in scientific or academic roles seeking to understand or apply ML techniques to their work
- Business Professionals: Managers or decision makers who want to understand the capabilities and limitations of machine learning and how it can impact their business.
- Freelancers: Developers or consultants looking to expand their services by mastering machine learning tools and frameworks.
Python & TensorFlow: Deep Dive into Machine Learning course details
- Publisher: Udemy
- teacher: Meta Brains
- Training level: beginner to advanced
- Training duration: 3 hours and 1 minute
- Number of courses: 34
Course topics Python & TensorFlow: Deep Dive into Machine Learning
Python & TensorFlow: Deep Dive into Machine Learning course prerequisites
- Basic Python Knowledge: Familiarity with Python’s syntax and basic programming constructs
- Foundational Math Skills: Understanding of algebra, and a basic grasp of calculus and statistics would be beneficial, especially for grasping underlying algorithms
- Computer with Internet Access: To download required software, access course materials, and run Python and TensorFlow
- Enthusiasm for Machine Learning: A keen interest to delve into the intricacies of ML and DL
Python Environment Setup: Having an environment like Jupyter Notebook or any IDE suitable for Python (eg, PyCharm) could be advantageous - Basic Understanding of Data Structures: Familiarity with lists, arrays, matrices, etc., given the data-centric nature of the course
- Logical & Analytical Thinking: Ability to approach problems methodically and think critically
Willingness to Experiment: Given the hands-on nature of ML and TensorFlow projects, being open to trying things out and learning from mistakes is crucial
Course images
Sample video of the course
Installation guide
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download link
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