Jianxi Gao’s Post

Curious about neural networks? Our FREE course notes are your guide to the basics of this pivotal machine learning tool. We start with core concepts, simplifying neural networks for anyone keen to understand and apply them. Our Course Notes are designed for budding data scientists and engineers who want to incorporate machine learning into their skills. They cover everything from algorithm building blocks to the nuances of regression and classification. Get a solid grasp on key machine learning concepts that will serve as the foundation for more complex models. FREE Download Link 👉 https://bit.ly/3WkOEKO #machinelearning #neuralnetworks #datascienceeducation #mlalogorithms #learndatascience

I am delighted to announce that our latest publication, "Forecasting Stock Trends with Feedforward Neural Networks," presented at #FedCSIS 2024—the 19th Conference on Computer Science and Intelligence Systems—has received a Special Award in the #FedCSIS 2024 Data Science Challenge. Stock market prediction is a complex yet critical task that significantly contributes to the stability and efficiency of financial markets by providing essential insights into market trends and movements. In this work, we propose a straightforward yet powerful model utilizing feedforward neural networks to address this challenge. Our approach draws on recent advances in machine learning and deep learning to analyze and process large financial datasets, achieving promising results in forecasting stock trends. Direct link to the paper: https://lnkd.in/dJCDzTV3 #FedCSIS #stockmarketprediction #artificialintelligence #computerscience #neuralnetworks #deeplearning #forecasting #classification #researchpaper #awards

Mamba vs. Transformers: A Faster and Smarter Approach to Long-Sequence Processing Mamba is a new deep learning model that improves on Transformers, which are widely used for tasks like language and image processing. Unlike Transformers, which slow down and use a lot of memory when working with very long sequences (like text or audio with millions of words), Mamba uses a different method called Selective State Space Models (SSMs). This makes it much faster and more efficient for handling long data. While Transformers are powerful but struggle with long sequences, Mamba can work on tasks like language, audio, and genomics with better speed and less memory, making it a great alternative for handling huge amounts of data. Read the paper : https://lnkd.in/ghiAGFac

🎓 Delighted to announce the completion of an intensive Convolutional Neural Networks certificate program! 🚀 Delved deep into cutting-edge CNN architectures, mastering advanced feature extraction and pattern recognition techniques pivotal in crafting precise predictive models. From real-world projects to theoretical foundations, I've honed my skills to drive data-driven solutions with confidence. Ready to leverage this expertise to tackle complex challenges and innovate in the realm of #DeepLearning, #MachineLearning, #DataScience, and #ComputerVision! 💡🌟 #ContinuousLearning

Proud to share that I’ve completed an intensive Artificial Intelligence course, equipping me with the latest skills and knowledge in machine learning, neural networks, and data science. This journey has been a blend of challenging concepts, practical projects, and innovative problem-solving. Ready to leverage this expertise to drive technological advancements and create intelligent solutions. #AIMastery #MachineLearning #DataScience #CareerGrowth #ContinuousLearning #AItoolsmasteryprogram #promptengineering

Proud to share that I’ve completed an intensive Artificial Intelligence course, equipping me with the latest skills and knowledge in machine learning, neural networks, and data science. This journey has been a blend of challenging concepts, practical projects, and innovative problem-solving. Ready to leverage this expertise to drive technological advancements and create intelligent solutions. #AIMastery #MachineLearning #DataScience #CareerGrowth #ContinuousLearning #AItoolsmasteryprogram #promptengineering

A great introduction to Graph Neural Networks!

🎉️Thrilled to share that I have completed the 𝐍𝐞𝐮𝐫𝐚𝐥 𝐍𝐞𝐭𝐰𝐨𝐫𝐤𝐬 𝐚𝐧𝐝 𝐃𝐞𝐞𝐩 𝐋𝐞𝐚𝐫𝐧𝐢𝐧𝐠 course by DeepLearning.AI, led by Andrew Ng. 🌠This course deepened my understanding of neural network architectures, backpropagation, forward propagation and optimization algorithms. It provided valuable insights into the building blocks of deep learning and how they power modern AI systems. 🚀Looking forward to apply these skills to real-world challenges. #AI #MachineLearning #DeepLearning #NeuralNetworks #DataScience #Technology #ComputerVision #GenerativeAI

Just finished the course “TensorFlow: Neural Networks and Working with Tables” by Jonathan Fernandes! Check it out: https://lnkd.in/dtXuZdKZ #neuralnetworks #tensorflow.

🌟This week, I completed the class COMP 381 - Machine Learning 🤖, culminating in a project focused on implementing Computer Vision 👁️🗨️. My team and I constructed 3 Machine Learning and Deep Learning models to identify facial emotions from videos 🎬 and images 🖼️. Our target was to compare the efficiency of classification models on the same task, including Convolutional Neural Network (CNN), Decision Tree, and K-nearest neighbors (KNN). Utilizing the transfer learning approach 💡, we successfully created the emotion recognition system based on the pre-trained face detection models (Haarcascades and MTCNN). The video below is a demo of the working CNN model on recognizing emotion through live videos I developed and trained on the FER 2013 dataset from Kaggle. If interested, you can find the project here: 👉 https://lnkd.in/gTSfz7Q8 #machinelearning #deeplearning #computervision #datascience #transferlearning #cnn #knn #decisiontree