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Data-Engineer-Nanodegree
implement All project in Data Engineer NanodegreeFreeRtos_examples
FreeRtos_examples using stm32 and freertos on system workbensh idelcd_driver_4bit
lcd_driver_4bit using atmega16Image-Data-Augmentation-with-Keras
Image Data Augmentation with Kerassetup-Big-data-cluster
setup big data cluster on dockerImage_Captioning
Image_Captioning using coco dataset and pretrained modelUdacity-Data-streaming-Nanodegree
Implement Data Streaming Project And Exercise in this nanodegree-Advanced-Lane-line-Finding
Advanced Lane Detection Project which includes advanced image processing to detect lanes irrespective of the road texture, brightness, contrast, curves etc. Used Image warping and sliding window approach to find and plot the lane lines. Also determined the real curvature of the lane and vehicle position with respect to centerahmed-hassan
shell using operating system linuxmultiplication-two-array
deploy_machine_learning_model
Deploy machine learning model using Streamlitsentiment-analysis_using_nlp
sentiment-analysis-keras using nlp algorithmsdynamic-programming-fibonanci
pretrained_model-
Transfer learning using pretrained model(inception_v3)insertion-sort-algorithm
data-analysis-project
TV, Halftime Shows, and the Big Game dataset from datacampclassification-using-data-regulrization
YOLO
using yolo liprary you can detect object with high accuracy by usind dnn which use in this lipraryInvestigate_TMDb_Movies
investigate movie dataset to analysis it using data analysis librarybuild_neural_network
build_neural_network using Mathematical equations and numby libraryfirst_project_for_classification
project classify disease into ten ouputAmazon_SageMaker_project
algorithm-code
bluetooth_driver
interface bluetooth_driver with atmega16ABehavioral-Cloning-Project
Behavioral Cloning Project for Self-Driving Car Nano Degree . The project includes designing a neural network and then training the car on the road in unity simulator. The CNN learns and clones the driving behaviortraffic-light-recognition
heep-sort
gpio_driver
stack-with-struct
merge-sort
classification-using-keras
ai project built in how can neural network able to classifiy between imageskeras_example
mini project from deep learning specialization (andrew course from coursera)-ahmedhasRegression_using_multiple-variable
ahmedhasRegression_using_multiple-variable based on library in python using numpy and pandas and matplotlibquick-sort-
linear-search
linked-list
search_algorithm
search_algorithm using ai (dfs-bfs-ucs-gready-a*) in graph and treeiot_project
iot project using dweet in java script and html and cssregression-using-one-variable
regression using one variablesdata_visulization
make data visulization using matplotlib and numby and pandas library using pythonfruit_ninga-game
fruit ninga game using javafxqueue-with-struct
lcd_driver
lcd_driver_using 8bit and avr microcontrollerpretrained_model-in-keras-for-image-classification
this kernel is comparison between accuracy to pretrained model in kerasMachine-Translation-from-English-to-France
build a deep neural network that functions as part of an end-to-end machine translation pipeline. Your completed pipeline will accept English text as input and return the French translationNatural-Language-Processing-in-TensorFlow
This repositories to load data in json and tokenize it to learn Rnn to complete patternproject_for_classify_emails
this project to classify email into (spam and good) email using support vector machine(svm) classifyTraffic-Sign-Classifier
you will use what you've learned about deep neural networks and convolutional neural networks to classify traffic signs. You will train and validate a model so it can classify traffic sign images using the German Traffic Sign Dataset. After the model is trained, you will then try out your model on images of German traffic signs that you find on the webapplying-neural_network-for-embeded-system
applying neural_network for arduino microcontroller usingclassification_for_two_variables
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