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via Udemy |
Go to Course: https://www.udemy.com/course/pythonmachinelearning/
Certainly! Here's a comprehensive review and recommendation for the course based on the provided details: --- **Course Review: Mastering Artificial Intelligence and Machine Learning for Beginners on Coursera** If you're new to the world of artificial intelligence (AI) and machine learning (ML), this course offers an incredible entry point that covers everything from basics to practical implementations. Funded by a successful Kickstarter, this course provides a rich, hands-on learning experience with a clear path to building real-world AI-powered applications. **What the Course Offers:** - **Comprehensive Content:** This course spans three levels—covering AI, machine learning, and mobile development—making it a one-stop-shop for beginners eager to delve into these transformative technologies. - **Practical Projects:** You will create three complete mobile applications—weather prediction, stock market prediction, and a text-response app. Building these apps from scratch and exporting them to Android Studio to be run on real devices gives you tangible results to showcase your skills. - **Tools and Technologies:** The course leverages industry-standard frameworks and tools such as TensorFlow, Python, Java, Android Studio, and PyCharm. This exposure ensures you gain relevant skills for the current job market. - **Beginner-Friendly Approach:** No prior experience? No worries. The course starts with the fundamentals of Python 3.6.2 and Java 8, with detailed instructions on installing and navigating PyCharm and Android Studio. The instructor's step-by-step tutorials are especially helpful for absolute beginners. - **Deep Dive into Machine Learning:** The course explains core concepts like neural networks, deep learning, and prediction algorithms, illustrating their real-world uses and importance. - **Hands-On Practice:** You will train, test, and evaluate models, gaining confidence in developing and deploying machine learning models. **Pros:** - Clear, structured, and beginner-friendly curriculum. - Extensive practical projects that reinforce learning. - Exposure to multiple programming languages and tools relevant to AI and mobile app development. - Supportive, step-by-step guidance suitable for those with no coding experience. - The inclusion of both theoretical knowledge and practical implementation makes it ideal for learners seeking both understanding and skills. **Cons:** - The breadth of content might be overwhelming for those who prefer deep dives into fewer topics. - As a beginner course, some concepts might still seem advanced, requiring additional self-study for mastery. **Recommendation:** This course is highly recommended for beginners interested in AI, machine learning, and mobile development with Java and Python. Its project-based approach not only teaches you theoretical concepts but also enables you to create real applications, boosting your portfolio and employability. If you're motivated to learn how AI is applied in apps and want practical skills to start building your own projects, this course is an excellent choice. --- **In summary:** Whether you're just starting out or looking to strengthen your foundational knowledge in AI and ML, this Coursera course offers a comprehensive, engaging, and hands-on learning experience. With its supportive instruction and real-world projects, you’ll be well-equipped to enter the exciting world of artificial intelligence and mobile app development. --- Feel free to ask if you'd like a shorter summary or specific details!
Go through 3 ultimate levels of artificial intelligence for beginners!Learn artificial intelligence, machine learning, and mobile dev with Java, Android, TensorFlow Estimator, PyCharm, and MNIST. Woah! That's a lot of content for one course.This course was funded by a wildly successful KickstarterUse Google's deep learning framework TensorFlow with Python. Leverage machine learning to improve your appsPrediction Models MasterclassBy the end of this course you will have 3 complete mobile machine learning models and apps. We will build a simple weather prediction project, stock market prediction project, and text-response project. For each we will build a basic version in PyCharm, save the trained model, export the trained model to Android Studio, and build an app around model.No experience? No problemWe'll give you all necessary information to succeed from newbie to pro. We will install PyCharm 2017.2.3 and explore the interface. I will show you every step of the way. You will learn crucial Python 3.6.2 language fundamentals. Even if you have coding knowledge, going back to the basics is the key to success as a programmer. We will build and run Python projects. I teach through practical examples, follow-alongs, and over-the-shoulder tutorials. You won't need to go anywhere else.Then we will install Android Studio 3 and explore the interface. You will learn how to add a simulator and build simple User Interfaces (UIs). For coding, you will learn Java 8 language fundamentals. Java is a HUGE language that you must know, and I will tell you all about it. We will build and run Android projects directly in the course, and you will have solid examples to apply your knowledge immediately.Complete Image Recognition and Machine Learning for BeginnersWith this course I will help you understand what machine learning is and compare it to Artificial Intelligence (AI). Together we will discover applications of machine learning and where we use machine learning daily. Machine learning, neural networks, deep learning, and artificial intelligence are all around us, and they're not going away. I will show you how to get a grasp on this ever-growing technology in this course. We will explore different machine learning mechanisms and commonly used algorithms. These are popular and ones you should know.Next I'll teach you what TensorFlow 1.4.1 is and how it makes machine learning development easier. You will learn how to install TensorFlow and access its libraries through PyCharm. You'll understand the basic components of TensorFlow.Follow along with me to build a complete computational model. We'll train and test a model and use it for future predictions. I'll also show you how to build a linear regression model to fit a line through data. You'll learn to train and test the model, evaluate model accuracy, and predict values using the model.Stock Market, Weather & Text - Let's Go!