Steven Hedges’ Post

Hello Connections! 😊 Today, I am excited to share the completion of my latest project in the AI field: YouTube Analysis Using Python. 📊🔍 In this project, I delved deep into YouTube's data, leveraging advanced data analytics to uncover key insights and trends through real-time data scraping and analysis. Here’s a glimpse of what I have accomplished: https://lnkd.in/dJipG6Dj #DataScience #MachineLearning #Python #YouTubeAnalytics #AI #trending #ArtificialIntelligence

If you're like me and sometimes run into GPU limitations on your local machine, I Tried a neat workaround to run Ollama in Google Colab, allowing you to leverage Colab's resources for your AI projects. You can find how To set it up Here : https://lnkd.in/deU6-HHY #GenerativeAI #LLM #RAGsystems #ArtificialIntelligence #MachineLearning #DataScience #AIResearch #TechInsights #AIApplications #AICommunity #Ollama #Python

🚀 Exploring Non-Euclidean Clustering Algorithms! 🌐 Excited to share my latest project on clustering in non-Euclidean spaces using spherical and hyperbolic distance metrics. Dive into the code and visualizations to see how we can push the boundaries of traditional clustering methods. Check it out on Colab: https://lnkd.in/gY-D6YF3 #DataScience #MachineLearning #Clustering #NonEuclidean #AI #Python

Lectures 10, 11, and 12 Highlights: Advanced AI with Sir Irfan Malik As-salamu alaykum! Today, in our Advanced AI Learning Journey, we are covering three essential lectures with Sir Irfan Malik. In these sessions, we will discuss: - Conditional statements - Loops (while loops and for loops) - User-defined functions in Python - Open Ai To enhance your learning experience, we've prepared a Colab notebook with practical exercises. Check out the link below and follow along with the exercises. 📚 Colab Notebook Link of Lecture 10 https://lnkd.in/d_fNBGFy 📚 Colab Notebook Link of Lecture 11 https://lnkd.in/dA67vN-P 📚 Colab Notebook Link of Lecture 12 https://lnkd.in/dEfsjd5v Let's continue building our Python skills together! #AI #Python #Functions #Loops #ConditionalStatements #LearningJourney #ZeonSolutions #TechSkills #ContinuousLearning

Hey connections.....I am thrilled to share that I've started a new journey in career with CoralFlow - "Intensive Gen AI training program"!! In week 1,I have gained a knowledge about Functions, Libraries, OOPS in Python. Here is my week 1 assignment- https://lnkd.in/gb-ENNMk Thanks to my mentors Vishnuraj Saravanan Sunil N Yogeshwaran Singarasu for their support in explaining the concepts. #coralflow #genai #30daystraining #python

Check on my Cat and Dog Image classifier using TensorFlow (Machine Learning with Python)

I've been looking into python libraries to extract stems from songs. This would allow me to listen to the isolated bass part to learn the song; as well as play along with songs without the bass in the mix. After having issues getting Spleeter to work on my Windows machine, I found this python notebook. I'm also testing pytube and youtube-dl to extract songs from YouTube to run as inputs into Spleeter. Long-term, I'd like to find some libraries to identify the key of the song and then change the key. Here is an example of calling spleeter: > !spleeter separate -p spleeter:4stems -o output/ file.mp3 #music #python #ai

🚀 Excited to Share My Journey with NumPy! 🚀 In the past two days, I've dived deep into NumPy, covering key areas like: Array creation and manipulation Indexing, slicing, and reshaping Performing arithmetic and aggregate functions Dot products and matrix operations Check out my practice notebook for details: https://lnkd.in/daURzXtW #DataScience #NumPy #LearningJourney #Python

Make Pandas 150X faster with one line of code... ...from NVIDIA. Grab it here: cuDF is a GPU DataFrame library for loading joining, aggregating, filtering, and otherwise manipulating data. Here's how it works: %load_ext cudf.pandas That's it! Try it: https://lnkd.in/dWQepmg8 Download it: https://lnkd.in/dbtW5yV Looking to start using Python for market data analysis? Here's a free Ultimate Guide with everything you need to get started. Join the 1,000s of people who finally started with Python after reading it: https://lnkd.in/eNtRcYHX

The following sections are implemented from Python Machine Learning book📚 🔉Section#1 Building a perceptron. 🔉Section#2 Using a desired subset of the dataset. 🔉Section#3 Distribution of flower examples using two features as the axes. 🔉Section#4 Plotting the misclassification errors vs. the number of epochs in the training process of the perceptron. 🔉Section#5 Visualization of the decision boundaries. 🔉Section#6 Builiding an ADALINE using a perceptron. 🔉Section#7 The relationship between a good learning rate and an optimal convergence. 🔉Section#8 Standardization implementation on ADALINE. 🔉Section#9 Updating the weights of ADALINE neuron by Stochastic Gradient Descent 🔉Section#10 Training a Perceptron by Scikit-learn API Link: https://lnkd.in/dfP2hhKr #cs_internship  #machine_learning  #step7