Sidharth @PyCodeMates

@hrishio @alexalbert__ It so true that Claude will say what it thinks to face without any drama.

Q-Drive: Self-Play Car Game Using Deep #Reinforcementlearning. The project aims to understand the effectiveness of #DeepQLearning in continuous environments. #ArtificialInteligence #DeepLearning #NeuralNetworks #MachineLearning Source Code: github.com/sidharth72/Q-D…

Live Link: jobsum.streamlit.app Source Code: github.com/sidharth72/Job…

The chat tab is where we can talk to Gemini model, which summarizes and answers our questions based on the ton of job descriptions we've extracted.

There are three main tabs to interact with, the first one is the extraction tab, this tab allows us to extract data from popular job platforms.

It can also suggest the best ways to optimize your journey to reach the goal. This process saves you valuable time that would otherwise be spent manually reading through numerous job postings.

𝑅𝑒𝑎𝑑𝑖𝑛𝑔 ℎ𝑢𝑛𝑑𝑟𝑒𝑑𝑠 𝑜𝑓 𝑡ℎ𝑜𝑢𝑠𝑎𝑛𝑑𝑠 𝑜𝑓 𝑗𝑜𝑏 𝑑𝑒𝑠𝑐𝑟𝑖𝑝𝑡𝑖𝑜𝑛𝑠 𝑤𝑖𝑡ℎ𝑖𝑛 𝑚𝑖𝑛𝑢𝑡𝑒𝑠 𝑜𝑟 𝑠𝑒𝑐𝑜𝑛𝑑𝑠 𝑖𝑠 𝑛𝑜𝑡 ℎ𝑢𝑚𝑎𝑛𝑙𝑦 𝑝𝑜𝑠𝑠𝑖𝑏𝑙𝑒, 𝑏𝑢𝑡 𝐴𝐼 𝑐𝑜𝑢𝑙𝑑 𝑑𝑜 𝑡ℎ𝑎𝑡.

The AI can extract essential information such as required skills, experience levels, and interview insights that are common among hundreds of thousands of job descriptions and can even give tutorials and guides to refer to.

The JobSum tool leverages an advanced 𝐋𝐋𝐌 𝐦𝐨𝐝𝐞𝐥 (𝐆𝐞𝐦𝐢𝐧𝐢 𝟏.𝟎 𝐏𝐫𝐨: 𝐆𝐨𝐨𝐠𝐥𝐞 𝐃𝐞𝐞𝐩𝐌𝐢𝐧𝐝) API to analyze and understand hundreds of job descriptions in a matter of seconds.

It utilizes data fetched from popular job platforms like #Indeed, LinkedIn, #Glassdoor, ZipRecruiter, and more, and provides a personalized and comprehensive job summary for each search query.

𝐉𝐨𝐛𝐒𝐮𝐦 is a job summarization and interactive app built using Streamlit designed to make your job search process easier and more efficient.

#youtube video summarization & Chat #ai #chatbot #gpt-3 #gradio #langchain Live: lnkd.in/gmASdYrW Source Code: lnkd.in/gSr-5y_p Project: lnkd.in/g7ZgCNAP

#AI is transforming finance by learning to #trade stocks through #DeepReinforcementLearning. Using a custom environment and technical indicators, the neural network agent learns to make better trades after a million timesteps of training. suite.pycodemates.com/trading-ai-usi…

Hi everyone, I recently built a Convolutional Neural Network (CNN) from scratch using NumPy, just for fun! 😁 This is one of the activities I always engage in during my free time, and it has been an excellent way to gain a deeper understanding of how the…lnkd.in/gEkSCM2B

Mini Series #MLMiniSeries #RNN A Recurrent Neural Network (RNN) is a type of neural network that processes sequences of inputs and produces sequences of outputs. It is commonly used in natural language processing, image recognition, and time series analysis.

#MLminiSeries #CNN: A Convolutional Neural Network is a type of deep learning AI used for image recognition & classification tasks. It takes an input image, passes it through multiple convolution layers, and produces an output of class probabilities. #AI #DeepLearning

#MLminiSeries #ActivationFunctions An activation function is a non-linear transformation that is applied to the input of a node in a neural network to determine the output of the node. It is a mathematical function used to determine the output of a neural network.

#MLminiSeries #Backpropagation Backpropagation is an algorithm used to calculate the error contribution of each neuron after a batch of data. It is used in supervised learning to update the weights and biases of the neural network.

#MLminiSeries #FeedforwardNN A feedforward neural network is a type of artificial neural network in which information flows only in one direction, from input to output, without forming a cycle. It is a basic type of artificial neural network.