100 days : Your Data Science and ML Degree — Part 2
Everything you need to know…
Welcome back peeps. Hope all’s well at your end. While I’m extremely busy with work; I target to write once every three days if my schedule allows. This post is a 100 days — your Data Science and ML degree ( Part 2) — mega compilation of Data Science and ML theory and projects that we have built till now and progressing forward — what to expect. You can use this as a starting point to advanced level and devise your own Data Science and ML degree ( PS: you don’t have to buy expensive courses to be able to learn/get into/ build data science and ML).
Part 1 ( Day 1- 71 ) of this series can be found here —
Lets dive in —
Day 72–100 : Build Projects
Complete Data Preprocessing and Data Visualization with Projects — Mega Compilation Part 2
Data visualization and Clustering
Data visualization and Clustering
Machine Learning Classification and a Project
Machine Learning Classification Project 2 ( Part 1)
Machine Learning Classification Project 2 ( part 2)
Highly Recommended Data Science and Machine Learning Courses that you MUST take ( with certificate) —
Quick Recap : 30 days of Natural Language Processing ( NLP) with Projects Series
Cluster Analysis using Python — Part 1
Detailed Analysis of the Netflix Content
Detailed Crypto Analysis
Machine Learning Clustering in detail with a project 2 ( part 1)
Machine Learning Clustering in detail with a project 2 ( part 2)
Multiple linear regression with a project
Logistic regression with a project
Logistic regression with another project
Hyperparameter Tuning with Keras Tuner
Analyzing Video using Python, OpenCV and NumPy
ANN, Linear Regression, Decision Tree Regression and Random Forest with a project
Principal Component Analysis with a project
Bidirectional Encoder Representations from Transformers ( BERT) with a project
Neural Network with a project
Build Machine Learning Pipelines( With Code)
Recurrent Neural Network with Keras
RNN and Tensorflow with a project
Custom Layers in Keras
Clustering Geolocation Data in Python using DBSCAN and K-Means
Long Short Term Memory networks (LSTM) with Keras
Facial Expression Recognition using Keras
Implement Tokenization, POS tagging, Chunking, Named Entities Recognition ( NER)
Language Classification with a project
Part 3 : Coming Soon!
Some of the other best Series —
100 days : Your Data Science and Machine Learning Degree Series with projects
Complete Data Visualization and Pre-processing Series with projects
Projects Videos —
All the projects, data structures, SQL, algorithms, system design, Data Science and ML , Data Analytics, Data Engineering, , Implemented Data Science and ML projects, Implemented Data Engineering Projects, Implemented Deep Learning Projects, Implemented Machine Learning Ops Projects, Implemented Time Series Analysis and Forecasting Projects, Implemented Applied Machine Learning Projects, Implemented Tensorflow and Keras Projects, Implemented PyTorch Projects, Implemented Scikit Learn Projects, Implemented Big Data Projects, Implemented Cloud Machine Learning Projects, Implemented Neural Networks Projects, Implemented OpenCV Projects,Complete ML Research Papers Summarized, Implemented Data Analytics projects, Implemented Data Visualization Projects, Implemented Data Mining Projects, Implemented Natural Leaning Processing Projects, MLOps and Deep Learning, Applied Machine Learning with Projects Series, PyTorch with Projects Series, Tensorflow and Keras with Projects Series, Scikit Learn Series with Projects, Time Series Analysis and Forecasting with Projects Series, ML System Design Case Studies Series videos will be published on our youtube channel ( just launched).
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Happy learning and keep coding :)
Follow for more updates, stay tuned and of-course let me end this post with a quote by Steve Jobs ;)
“Your work is going to fill a large part of your life, and the only way to be truly satisfied is to do what you believe is great work. And the only way to do great work is to love what you do. If you haven’t found it yet, keep looking. Don’t settle. As with all matters of the heart, you’ll know when you find it.”
