Tag: deep learning

  • Overview of AWS Tech Portfolio 2023

    Overview of AWS Tech Portfolio 2023

    This article provides with an overview of 50+ Amazon Web Services (AWS) 2023. AWS is the leading vendor of cloud services and infrastructure, dominating the cloud computing market: Amazon net sales increased by 15% to $127.1 billion in Q3 2022 as compared to $110.8 billion in Q3 2021. AWS segment sales increased by 27% year-over-year to reach…

  • Deep Reinforcement Learning (DRL) on $MO 8.07% DIV USA Stock Data 2022-23

    Deep Reinforcement Learning (DRL) on $MO 8.07% DIV USA Stock Data 2022-23

    MLQ.ai: In fact, many AI experts agree that DRL is likely to be the best path towards AGI, or artificial general intelligence. Spinning Up in DRL at OpenAI: “We believe that deep learning generally—and DRL specifically—will play central roles in the development of powerful AI technology.” Key assumptions and limitations of the DRL framework: Key…

  • Risk-Return Analysis and LSTM Price Predictions of 4 Major Tech Stocks in 2023

    Risk-Return Analysis and LSTM Price Predictions of 4 Major Tech Stocks in 2023

    The open-source Python workflow breaks down our investigation into the following 4 steps: (1) invoke yfinance to import real-time stock information into a Pandas dataframe; (2) visualize different dataframe columns with Seaborn and Matplotlib; (3) compare stock risk/return using historical data; (4) predict stock prices in 2023 with the trained LSTM model. Input Data Let’s…

  • AI-Driven Object Detection & Segmentation with Meta Detectron2 Deep Learning

    AI-Driven Object Detection & Segmentation with Meta Detectron2 Deep Learning

    Method Computer Resources Python 3 Google Compute Engine backend (GPU) Install Detectron2 !python -m pip install pyyaml==5.1 import sys, os, distutils.core # Note: This is a faster way to install detectron2 in Colab, but it does not include all functionalities. # See https://detectron2.readthedocs.io/tutorials/install.html for full installation instructions !git clone ‘https://github.com/facebookresearch/detectron2’ dist = distutils.core.run_setup(“./detectron2/setup.py”) !python -m pip install {‘ ‘.join([f”‘{x}’” for x in dist.install_requires])} sys.path.insert(0, os.path.abspath(‘./detectron2’)) # Properly install detectron2. (Please do not install twice in both ways) # !python -m pip install ‘git+https://github.com/facebookresearch/detectron2.git’ Import Libraries import torch, detectron2 !nvcc –version TORCH_VERSION = “.”.join(torch.__version__.split(“.”)[:2]) CUDA_VERSION = torch.__version__.split(“+”)[-1] print(“torch: “, TORCH_VERSION, “; cuda: “, CUDA_VERSION) print(“detectron2:”, detectron2.__version__) nvcc: NVIDIA (R) Cuda compiler driver Copyright (c) 2005-2022 NVIDIA Corporation Built on Tue_Mar__8_18:18:20_PST_2022 Cuda compilation tools, release 11.6, V11.6.124 Build cuda_11.6.r11.6/compiler.31057947_0 torch: 1.13 ;…

  • Comparative ML/AI Performance Analysis of 13 Handwritten Digit Recognition (HDR) Scikit-Learn Algorithms with PCA+HPO

    Comparative ML/AI Performance Analysis of 13 Handwritten Digit Recognition (HDR) Scikit-Learn Algorithms with PCA+HPO

    Featured Photo by Torsten Dettlaff on Pexels The article consists of the following three parts: 3. Unsupervised ML using the Principal Component Analysis (PCA) for the dimensionality reduction within Parts 1 and 2. Our main goal is to build a text and graphics report comparing the main scikit-learn classification metrics: accuracy_score, classification_report (precision, recall, and…

  • Multi-Label Keras CNN Image Classification of MNIST Fashion Clothing

    Multi-Label Keras CNN Image Classification of MNIST Fashion Clothing

    The Fashion MNIST Dataset Fashion-MNIST is a dataset of Zalando’s article images—consisting of a training set of 60,000 examples and a test set of 10,000 examples. Each example is a 28×28 grayscale image, associated with a label from 10 classes: Each image pixel has a single pixel-value associated with it, indicating the lightness or darkness…

  • AI-Based ECG Recognition – EOY ’22 Status

    AI-Based ECG Recognition – EOY ’22 Status

    Featured Photo by cottonbro studio on pexels. Electrocardiography (ECG) is the method most often used to diagnose cardiovascular diseases. The recent study demonstrates that an AI is capable of automatically diagnosing the abnormalities indicated by an ECG. In this post we will review and illustrate how AI applies to ECG analysis to outperform traditional ECG analysis.…

  • Short-term Stock Market Price Prediction using Deep Learning Models

      This blog is about short-term stock market price trend prediction using a comprehensive deep learning LSTM model. Results show that the model achieves overall high accuracy for stock market trend prediction. The following end-to-end sequence provides the detailed Python/Jupyter workflow from data processing to prediction, including the data exploration: 1. Data Preparation Phase #import libraries import…

  • About

      What is ML? Machine Learning (ML) is defined as follows: A code learns from experience E with respect to a task T and a performance measure P, if its performance on T, as measured by P, improves with E. [1].   Example 1: your code monitors spam and classifies emails as spam or not…