|
via Udemy |
Go to Course: https://www.udemy.com/course/hands-on-neural-networks-build-machine-learning-models/
Certainly! Here's a comprehensive review and recommendation for the course: --- **Course Review and Recommendation: Hands-On Neural Networks: Build Machine Learning Models by Nimish Narang (Mammoth Interactive)** If you're looking to gain practical experience in building neural network models with a focus on real-world applications, **"Hands-On Neural Networks: Build Machine Learning Models"** on Coursera is an excellent choice. Taught by Nimish Narang, a versatile cross-platform developer with extensive experience in machine learning, Java, Android, and more, this course offers a granular, project-based approach to mastering neural networks. ### Course Highlights: - **Project-Based Learning:** The course centers around building two comprehensive projects from start to finish, ensuring hands-on experience: 1. **Credit Card Fraud Detection:** Participants will develop a model capable of analyzing transaction data to predict whether a transaction is fraudulent or legitimate. The curriculum guides you through dataset exploration, manipulation, and constructing a neural network that outputs both confidence scores and binary classifications. 2. **Stock Market Prediction:** You will create a simplified model to forecast whether a stock's price will go up or down the next day based on trading volume. This project emphasizes short-term prediction and data preprocessing using real historical stock data. - **Data and Resource Curation:** The course comes with curated datasets, including credit card transaction data and stock market CSV files, allowing learners to follow along seamlessly without worrying about sourcing data. - **Teaching Approach:** Nimish ensures each step is thoroughly explained, making complex topics accessible even for beginners. The course covers building computational graphs, manipulating datasets, and deploying models in a practical environment. - **Additional Expertise:** Nimish Narang's background as a prolific content creator in machine learning and mobile development assures you are learning from an experienced instructor with a passion for clear, effective teaching. ### Who Is This Course For? - Beginners eager to get their hands dirty with neural network projects. - Developers interested in machine learning applications such as fraud detection and stock prediction. - Anyone looking for a practical, project-oriented introduction that they can expand upon later. ### Pros and Cons: **Pros:** - Accessible for beginners with no prior deep learning experience. - Clear, step-by-step instructions. - Real datasets with realistic scenarios. - Focus on building functional models that can be expanded. **Cons:** - The projects are simplified and meant as an introduction — advanced learners might want more complex models. - Some programming familiarity is recommended for best results. ### Final Recommendation: If you are aiming to learn neural networks through practical projects with clear guidance, this course is highly recommended. It provides foundational skills that can be built upon in more advanced contexts and is ideal for those who prefer learning by doing. The combination of curated datasets, detailed explanations, and real-world application makes this an excellent starting point for aspiring machine learning practitioners. --- **Enroll today** to start building your own neural networks and gain valuable skills that you can apply across various domains! ---
Build 2 complete projects start to finish - with each step explained thoroughly by instructor Nimish Narang from Mammoth Interactive.Hands-On Neural Networks: Build Machine Learning Models was funded by a #1 project on KickstarterNimish is our cross-platform developer and has created over 20 other courses specializing in machine learning, Java, Android, SpriteKit, iOS and Core Image for Mammoth Interactive. When he's not developing, Nimish likes to play guitar, go to the gym and laze around at the beach. Project #1 - Learn to construct a model for credit card fraud detection. Our model will take in a list of transactions, some fraudulent and some legitimate. It will output the percentage at which it can calculate fraudulence and legitimacy, how accurate it is. We will also modify the model so that it output whether a specific transaction is fraudulent or legitimate if we pass them in one by one.We will explore a dataset so that you fully understand it, and we will work on it. It's actually pretty hard to find a dataset of fraudulent/legitimate credit card transactions, but we at Mammoth Interactive have found everything for you and curated a step by step curriculum so that you can build alongside us.We will manipulate the dataset so that it will be easy to feed into our model. We will build a computational graph with nodes and functions to run input through the mini neural network.Machine Learning Projects Using Tensorflow - Mammoth InteractiveProject #2 - Learn to build a simple stock market prediction model that will predict whether the price stock will go up or down the next morning based on the amount of volume exchange for a given dayAny kind of global event can completely affect how stock prices fluctuate. As such we will build a simple model that only take in the volume exchange for a particular day and will only be used for day trading - choosing whether to buy or sell at the end of the day. It is short term prediction.We will NOT build a huge neural network that takes in thousands of data points and hours to train. We will build a simple model for you to expand upon. You will learn how to go through building a Tensorflow project and how you would get started with a stock prediction task.You will get a solid base that you can expand upon. We will take previous stock data from the Investing site. Included are 8 CSV sheets for you to use to train and test your model for four different stocks.Enroll now in Hands-On Neural Networks: Build Machine Learning Models with Mammoth Interactive