Benniah

Absenteeism-Business-Case

Preprocessing , Machine Learning , Integration , Deployment

Airflow_setup

Installing Airflow ---> Manual Vs Docker

CLUSTERING-with-GEODATA

BERLIN , ATMS , Cluster Analysis

data-engineer-roadmap

Roadmap to becoming a data engineer in 2021

Flask_API_Snowflake

A simple API built with Flask for fetching data from Snowflake ✲

Full-Exercise-Linear-Regression-

SKLearn , Training & Testing , Creating Dummies , Assumptions , VIF , Residuals , and more

MACHINE-LEARNING---MODEL-DEV

SLR , MLR , Polynomial R , Training Model , Prediction , Decision

ML-BusinessCase-Audiobooks

Building an Algorithm to predict if users are likely to make another purchase

Neural-Networks-_-Basic

Building a Machine Learning Algorithm using randomly generated data , Loss Function , Deltas , Gradient Decent Rule

Space-Exploration-NLP

A lab containing various exercises, concepts and advanced NLP with Spacy

Benniah/data-engineer-roadmap

Roadmap to becoming a data engineer in 2021

Benniah/NLP-Tokenization-LargeDataSet

In this Notebook, we apply the same Tokenization and Sequencing principles to a Large Corpus of Text

Benniah/TimeSeries-CNN

1D Convolutional layer Vs Full Convolutional layer (Best Results) ---Adjusted learning rates & Dilation Rates

Benniah/TRANSFER_LEARNING_FLOWERS

Classification of Flowers using the MobileNET model through the transfer learning technique

Benniah/Airflow_setup

Installing Airflow ---> Manual Vs Docker

Benniah/Flask_API_Snowflake

A simple API built with Flask for fetching data from Snowflake ✲

Benniah/Space-Exploration-NLP

A lab containing various exercises, concepts and advanced NLP with Spacy

Benniah/CNN_FashionMNIST

A convolutional Neural Network using the Fashion MNIST dataset

Benniah/Data_Preprocessing_Essentials

Benniah/Dog_Vs_Cat

Image classification of Dogs and Cats using CNNs and Augmentation

Benniah/Flower_Classification

Flower Classification using CNNs

Benniah/merge_requirements

merged-requirements

Benniah/NLP-ComapringModels

Using LSTMS , CNNs , GRUs for a larger dataset

Benniah/NLP-Padding-Truncating

Preparing Text , Applying Padding and Truncation to obtain sequences of equal length

Benniah/NLP-SUBWORDS

In this Notebook , we break down our text into subwords and check how it impacts our Model

Benniah/NLP-Tokenization

A quick introduction to the Tokenization of Text and Sequencing (Ordering Text) , How to deal with OOV( Out of Vocabulary Text )

Benniah/NLP-TweakingYourModel

In this Notebook , we tweak certain variables of our initial model such as the Vocabulary size , embedding dimension and Maximum length to yield Better results

Benniah/NLP-WordEmbeddings-Sentiment

We used a basic neural network together with word embeddings to predict Sentiment

Benniah/PDF_TEXT_EXTRACTION

Extracting text from PDF using python and converting them into keywords for further analysis

Benniah/PySpark

Some Sample Apache Spark Code for Data Engineering and Analytics

Benniah/Saving_Loading_Downloading-MODELS

Various ways of Saving , Loading and Downloading machine Learning Models

Benniah/Starwars_API_Request

Making requests to SWAPI using Pagination

Benniah/TimeSeries-Introduction

Common patterns in Time Series data : Trends , Series , Seasonality ,Noise

Benniah/TimeSeries-LSTM

Forecasting with an LSTM

Benniah/TimeSeries-MovingAverage

Computes the mean of the past values within a particular time window

Benniah/TimeSeries-NaiveForecasting

Splitting into Training and Validation

Benniah/TimeSeries-RecurrentNeuarlNetworks

Simple RNNS , Sequence to Sequence and Sequence to Vector

Benniah/TimeSeries-SimpleMachineLearning

Applying some simple machine learning in forecasting. Made use of learning rate and early stopping techniques to yield better Mean absolute error values. Also made use of dense layers.

Benniah/TimeSeries-Stateful_RNNs

Forecasting using stateful RNNs.

Benniah/TimeSeries-TimeWindows

Creating Time windows , Converting data set to Tensors , Creating inputs/Targets , "SuperFunction containing all steps"