mohd-faizy/Machine_Learning_with_Python

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mohd-faizy/Machine_Learning_with_Python

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Machine Learning can be an incredibly beneficial tool to uncover hidden insights and predict future trends. This repository Contain tools needed to get started with supervised and unsupervised learning.

Probabilistic-Deep-Learning-with-TensorFlow

Probabilistic Deep Learning finds its application in autonomous vehicles and medical diagnoses. This is an increasingly important area of deep learning that aims to quantify the noise and uncertainty that is often present in real-world datasets.

Jupyter Notebook

06P_Sentiment-Analysis-With-Deep-Learning-Using-BERT

Finetuning BERT in PyTorch for sentiment analysis.

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learn_python

This is a public repository of Jupyter notebooks with introductory tutorials on different aspects of Python programming. Please star us if you think it is useful:

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CAREER-TRACK-Data-Scientist-with-Python

This Repo contains tools that allow us to import, clean, manipulate, and visualize data —Includes Python libraries, like pandas, NumPy, Matplotlib, and many more to work with real-world datasets to learn the statistical and machine learning techniques.

Jupyter Notebook

DataScience-Projects

Projects : DataScience, Artificial intelligence, Machine learning, Deep Learning

09P_Detecting_COVID_19_with_Chest_X-Ray_using_PyTorch

Detecting COVID-19 with Chest X-Ray using PyTorch from COVID-19 Radiography Dataset on Kaggle

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02P_Project_Image_Classification_with_CNNs_using_Keras

Training a CNN in Keras with a TensorFlow backend to solve Image Classification problems

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Machine-Learning-Algorithms

This Repository consist of some popular Machine Learning Algorithms and their implementation of both theory and code in Jupyter Notebooks

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ML-DS-OneNote

Machine-Learning/Data-Science in one Notebook

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Hyperparameter-Tuning-with-Microsoft-Network-Intelligence-Toolkit-NNI

Hyperparameter Tuning with Microsoft NNI to automated machine learning (AutoML) experiments. The tool dispatches and runs trial jobs generated by tuning algorithms to search the best neural architecture and/or hyper-parameters in different environments like local machine, remote servers and cloud.

Machine-Learning-Scientist-with-Python

Machine Learning - - Supervised, Unsupervised, and deep learning. Processing data for features, training models, assess performance, and tune parameters for better performance. In the process, you'll get an introduction to natural language processing, image processing, and popular libraries such as Spark and Keras.

Jupyter Notebook

DataScience-With-Python

This Repo contains tools that allow us to import, clean, manipulate, and visualize data —Includes Python libraries, like `pandas`, `NumPy`, `Matplotlib`, and many more to work with real-world datasets to learn the statistical and machine learning techniques.

Jupyter Notebook

04P-Classify-Radio-Signals-from-Outer-Space-using-Keras

The data we are going to use consists of 2D spectrograms of deep space radio signals collected by the Allen Telescope Array at the SETI Institute. We will treat the spectrograms as images to train an image classification model to classify the signals into one of four classes.

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M01_Mathematics_for-Machine_Learning_Linear_Algebra

Linear Algebra, Multivariate Calculus & PCA

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LearnWebTech

WebTechnologies: HTML, CSS, JavaScript

Data_Visualization_Python

Jupyter Notebook

Learn_Seaborn

Seaborn is a visualization library for Python that builds on matplotlib and pandas. It provides beautiful default styles and color palettes for different types of plots, such as histograms, distributions, regression, and matrix plots.

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M02_Mathematics_for-Machine_Learning_Multivariable_Calculus

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07P_Tumor-Diagnosis-Exploratory-Data-Analysis-on-Breast-Cancer-Wisconsin-DataSet

Tumor Diagnosis: Exploratory Data Analysis With Seaborn

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Learn_Pandas

pandas is a powerful Python library for data analysis and manipulation. It’s like a Swiss Army knife for handling structured data!

Jupyter Notebook

mohd-faizy.github.io

Data_Analysis_With_Python

Jupyter Notebook

feature-engineering-hacks

This repository contains a collection of hacks and tips for feature engineering. It is a great resource for anyone who wants to learn how to improve the performance of their machine learning models.

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Python-for-DataScience

Jupyter Notebook

01P_Project_Deep_Learning_for_Traffic_Sign_Classification

Traffic Sign Classification Using Deep Learning in Python/Keras

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Learn_Numpy

NumPy (short for Numerical Python) is a powerful Python library used for working with arrays, matrices, and numerical computations.

Jupyter Notebook

My_TensorFlow

A comprehensive repository of jupyter notebooks in Tensorflow/keras

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Deeplearning-One-Fourth-Labs

DeepLearning Repo.

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Learn_Matplotlib

Matplotlib is a powerful plotting library in Python that allows you to create static, animated, and interactive visualizations. It’s widely used for representing data graphically, making it easier to analyze and understand.

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Licenses-certifications

Licenses & certifications

TF01_Introduction-to-TensorFlow-for-AI-ML-and-DL

TensorFlow for building basic neural network for computer vision and use convolutions to improve your neural network.

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05P_Understanding_Deepfakes_with_Keras_Using_DCGAN

Understanding Deepfakes with Keras

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03P_Facial_Expression_Recoginition

Facial Expression Recognition with Keras!

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08P_COVID19_Data_Analysis_Using_Python

Data Analysis on COVID19 dataset, published by John Hopkins University

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Developing-Large-Language-Models

Dive into LLM development! Learn cutting-edge techniques behind models like OpenAI's GPT-4, Meta's LLaMA 2, Mistral-7B, and Anthropic's Claude. Master PyTorch, build transformers, & fine-tune pre-trained LLMs from Hugging Face.

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PyTorch-Essentials

Welcome to the Pytorch Essentials repository! This Repo aims to cover fundamental to advanced topics related to PyTorch, providing comprehensive resources for learning and mastering this powerful deep learning framework.

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12P_Fake_News_Detection_with_Machine_Learning

In this project, we will train a Bidirectional Neural Network and LSTM based deep learning model to detect fake news from a given news corpus.

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mohd-faizy

Blogging-Website-Using-Flask

This is the a Blogging Website created Using Flask

NLP_Projects

Welcome to the Natural Language Processing Repository! This repository is a collection of code examples, algorithms, and resources for Natural Language Processing (NLP). NLP is a field that focuses on the interaction between computers and human language, enabling machines to understand, analyze, and generate text.

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Natural_Language_Processing_in_Python

This repository contains the code and resources for the "Natural Language Processing in Python". This repository contains the core skills you need to convert unstructured data into valuable insights using NLP.

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11P_Classification-with-Transfer-Learning-in-Keras

Classification with Transfer Learning in Keras

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TF02_Convolutional-Neural-Networks-in-TensorFlow

Tensorflow with real-world images in different shapes and sizes, visualize the journey of an image through convolutions to understand how a computer “sees” information, plot loss and accuracy, and explore strategies to prevent overfitting, including augmentation and dropouts

TF04_Sequences-Time-Series-and-Prediction

Using Tensorflow to solve time series and forecasting problems. Implement best practices to prepare data for time series learning & using RNNs and ConvNets for predictions. Finally, applying Tensorflow to build a sunspot prediction model using real-world data!

TF03_Natural-Language-Processing-in-TensorFlow

Solving Natural Language Processing problems with TensorFlow. Represent text through tokenization so that it’s recognizable by a neural network. Using RNNs, GRUs, and LSTMs, for NLP tasks and train them to understand the meaning of the text. Finally, we use Tensorflow to train LSTMs on existing text to create original poetry and more!

Quantam-Machine-Learning

Quantum machine learning is an emerging interdisciplinary research area at the intersection of quantum physics and machine learning

Stats-with-Data

This repository is a resource for learning and applying statistics in data science. It contains code examples and explanations for many common statistical concepts, from descriptive statistics through regression and time series analysis.

Jupyter Notebook

Deep-Learning

Deep learning is part of a broader family of machine learning methods based on artificial neural networks with representation learning. Learning can be supervised, semi-supervised or unsupervised