How to become a Machine Learning Engineer?

Bhagirath Deshani — Wed, 20 Jul 2022 11:56:22 +0000

Step 1: Learn a Programming Language

Popular Programming Language for Machine Learning

Python

R Language

C++

Java

JavaScript

Go

Shell

Step 2: Learn Mathematics for Machine Learning

Importance of Mathematics topics needed for Machine Learning

(15%) Algorithm and Complexity

(15%) Multivariate Calculus

(35%) Linear Algebra

(25%) Probability and Statistics

(10%) Others

Having a basic understanding of Probability and Statistics is important when it comes to mastering Machine Learning.

Step 3: Learn Core Machine Learning Algorithms

Supervised Learning
Unsupervised Learning
Reinforcement Learning

1. Supervised Learning Algorithm :

Regression

Decision Tree

Random Forest

Classification

2. Unsupervised Learning Algorithm :

Clustering

Association Analysis

Hidden Markov Model

3. Reinforcement Learning Algorithm :

Supervised & Unsupervised

Regression

Decision Tree

Random Forest

Clustering

Categorical

Classification

Association Analysis

Hidden Markov Model

Step 4: Learn the basic Libraries for Mathematics & Data Handling

TensorFlow
Keras
PyTorch
Scikit-learn
Pandas
NumPy
Spark
NLTK
Theano
mxnet

Step 5: Learn Deep Learning

Deep learning is a subset of machine learning, which is essentially a neural network with three or more layers.
These neural networks attempt to simulate the behavior of the human brain albeit far from matching its ability allowing it to “learn” from large amounts of data.
While a neural network with a single layer can still make approximate predictions, additional hidden layers can help to optimize and refine for accuracy.
Deep Learning Applications :

Law enforcement

Image Recognition

Financial services

Customer service

Healthcare

Automatic Machine Translation

Step 6: Start Working on Projects

Machine Learning Projects Ideas :
- Amazon Product Review
- Sentiment Analysis
- Hate Speech Detection
- COVID-19 Vaccine Analysis
- WhatsApp Chats Analysis
- Dogecoin Price Prediction
- Social Media Ads
- Classification
- Spotify Recommendation System
- Bankruptcy Prediction Model
- Instagram Algorithm
- Netflix Data Analysis

Data Science and Data Scientist Requirements

Bhagirath Deshani — Thu, 14 Jul 2022 11:53:14 +0000

Data science uses the most powerful hardware, programming systems, and most efficient algorithms to solve the data related problems.

What is Data Science?

Data science is an interdisciplinary field that uses scientific methods, processes, algorithms and systems to extract knowledge and insights from noisy, structured and unstructured data and apply knowledge from data across a broad range of application domains.

In the other words, we describe a data science is all about:

Modeling the data using various complex and efficient algorithms
Visualizing the data to get a better perspective
Asking the correct questions and analyzing the raw data
Understanding the data to make better decisions and finding the final result

Data Scientist Requirements

There is a describe in 4 components.

Math & Statistics
Domain Knowledge & Soft Skills
Programming & Database
Communication & Visualization

1. MATH and STATISTICS

Machine Learning
Deep Learning
Statistical Modeling
Experiment Design
Bayesian Interface
Supervised Learning :
- Decision Trees
- Random Forests
- Logistic Regression
- Linear Regression
Unsupervised Learning :
- Clustering
- Dimensionally Reduction
Optimization :
- Gradient Descent
- Variants

2. DOMAIN KNOWLEDGE and SOFT SKILLS

Passionate about the Business
Curious about Data
Influence without Authority
Problem Solver
Strategic
Proactive
Creative
Innovative
Collaborative

3. PROGRAMMING and DATABASE

Computer Science Fundamentals
Python / R
Databases SQL and NoSQL
Relational Algebra
Parallel Databases
Parallel Query Processing
MapReduce Concepts
Hadoop and Hive/Pig
Custom Reducers
Experience with xaaS like AWS

4. COMMUNICATION and VISUALIZATION

Able to engage with seniors
Translate data-driven insights into decision and actions
Visual art design
R packages like ggplot or lattice
Knowledge of any of Visualization tools
- Flare
- D3.js
- Tableau

DEV Community: Bhagirath Deshani