GitHub - wajeehulhassanvii/data_science_portfolio: data science portfolio basically containing many different micro and macro projeects which I implemented while learning data science from various sources and books employing machine learning, deep learning and data science techniques

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data science portfolio basically containing many different micro and macro projeects which I implemented while learning data science from various sources and books employing machine learning, deep learning and data science techniques

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Name		Name	Last commit message	Last commit date
Latest commit History 81 Commits
.ipynb_checkpoints		.ipynb_checkpoints
Google Colab		Google Colab
NLP		NLP
Scraping/dawn		Scraping/dawn
cloud/gcp		cloud/gcp
data manipulation/micro		data manipulation/micro
datasets		datasets
deep learning		deep learning
finance		finance
handson-ml2		handson-ml2
machine learning		machine learning
machine_learning_pipeline		machine_learning_pipeline
matplotlib		matplotlib
micro_projects		micro_projects
notebooks		notebooks
pyspark		pyspark
python		python
retail		retail
tuning_measurement_evaluation		tuning_measurement_evaluation
visualization		visualization
.gitignore		.gitignore
Machine Learning ALGOS		Machine Learning ALGOS
readme.txt		readme.txt

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.
├── analytics
├── aws
├── books
├── data manipulation
│   └── micro
│       ├── DATAFRAME AS A DICTIONARY.ipynb
│       ├── Handlling Missing Data.ipynb
│       ├── Hierarchical Indexing.ipynb
│       ├── INDEXERS LOC ILOC AND IX.ipynb
│       ├── Series and Dictionary.ipynb
│       ├── testing.ipynb
│       └── Ufuncs Index Preservation, axis.ipynb
├── deep learning
│   ├── dlaz
│   │   └── Artificial Neural Network - Bank Churn Data.ipynb
│   ├── handon-dl
│   └── nano-dl
│       ├── Sentiment_Classification_Projects.ipynb
│       └── Sentiment_Classification_Solutions.ipynb
├── finance
│   ├── Calculating Beyda.ipynb
│   ├── Multivariate Regression.ipynb
│   ├── Pandas rolling and expanding.ipynb
│   ├── time resampling.ipynb
│   └── time shifting.ipynb
├── Google Colab
├── images
├── kaggle
├── machine learning
├── mapreduce
├── matplotlib
│   └── micro
│       ├── 1D and 2D Histograms, Binnings, and Density.ipynb
│       ├── Customizing Plot Legends.ipynb
│       ├── Density and Contour plots.ipynb
│       ├── errorbars and continuous error.ipynb
│       ├── iris dataset visualization.ipynb
│       ├── Legend for Size of Points.ipynb
│       └── matplotlib general.ipynb
├── micro_projects
│   ├── 50 startups - multi linear regression ML.ipynb
│   ├── Decision Tree Classification ML.ipynb
│   ├── Decision Tree Regression ML.ipynb
│   ├── deep_learning
│   ├── Hierarchial Clustering - Mall csv ML.ipynb
│   ├── Kernel SVM  ML.ipynb
│   ├── KNN for dataset Social Network Ads ML.ipynb
│   ├── Logistic Regression - Social Network Ads ML.ipynb
│   ├── Mall Customer Clusters - Kmeans ML.ipynb
│   ├── Position Salary - Polynomial regression ML.ipynb
│   ├── Position Salary Prediction - Random Forest ML.ipynb
│   ├── Random Forest Classifier ML.ipynb
│   ├── Salary Prediction ML.ipynb
│   └── Support Vector Machine (Classifier) - Network Ads ML.ipynb
├── NLP
│   ├── 16_nlp_with_rnns_and_attention - google colab.ipynb
│   ├── 16_nlp_with_rnns_and_attention.ipynb
│   ├── images
│   │   └── nlp
│   └── Shakespeare HOML _ local.ipynb
├── numpy
├── python
├── retail
│   └── five-point summary .ipynb
├── scikit-learn
├── scipy
└── spark

28 directories, 39 files