Course Includes:
- Price: FREE
- Enrolled: 42699 students
- Language: English
- Certificate: Yes
- Difficulty: Advanced
Coupon verified 04:12 AM (updated every 10 min)
Course Folder
What You'll Learn
- Grasp fundamentals of machine learning
- deep learning
- and their applications
- Set up and navigate TensorFlow
- understanding its architecture and APIs
- Master supervised learning algorithms such as linear regression
- SVMs
- and decision trees
- Dive into unsupervised techniques including clustering and PCA
- Understand and construct neural networks
- including CNNs and RNNs
- using TensorFlow
- Evaluate and optimize ML models
- addressing overfitting and mastering hyperparameter tuning
- Deploy TensorFlow models in production environments
- Apply skills in a hands-on image classification project
- Transition from Python basics to advanced ML & TensorFlow applications
Requirements
- "Basic Python Knowledge: Familiarity with Pythons 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 (e.g.
- 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
Description
Welcome to our Python & TensorFlow for Machine Learning complete course. This intensive program is designed for both beginners eager to dive into the world of data science and seasoned professionals looking to deepen their understanding of machine learning, deep learning, and TensorFlow's capabilities.
Starting with Python—a cornerstone of modern AI development—we'll guide you through its essential features and libraries that make data manipulation and analysis a breeze. As we delve into machine learning, you'll learn the foundational algorithms and techniques, moving seamlessly from supervised 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'll uncover how to craft sophisticated neural network architectures, optimize models, and deploy AI-powered solutions. We don't just want you to learn—we aim for you to master. By the course's end, you'll not only grasp the theories but also gain hands-on experience, ensuring that you're industry-ready.
Whether you aspire to innovate in AI research or implement solutions in business settings, this comprehensive course promises a profound understanding, equipping you with the tools and knowledge to harness the power of Python, Machine Learning, and TensorFlow.
We're excited about this journey, and we hope to see you inside!
Who this course is for:
- Beginners in Data Science and AI: Individuals looking to kick-start their journey in machine learning and deep learning
- Python Developers: Programmers familiar with Python seeking to expand their skill set into AI and TensorFlow applications
- Data Analysts and Statisticians: Professionals looking to transition or incorporate machine learning techniques into their analysis workflows
- Tech Enthusiasts: Those curious about the latest trends in AI and wanting to get hands-on with TensorFlow and Python
- Students: Undergraduates or postgraduates studying computer science
- data science
- or a related field and wanting a comprehensive and practical overview
- Career Changers: Professionals from other fields wanting to pivot into data science or AI roles
- Researchers: Individuals in scientific or academic roles looking to understand or employ ML techniques in their work
- Business Professionals: Managers or decision-makers wanting to understand the capabilities and limitations of machine learning and how it can impact their business
- Freelancers: Developers or consultants looking to expand their service offerings by mastering machine learning tools and frameworks
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