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Sergey Savastiouk's Avatar
published in Blogs
Nov 14, 2021

Learning Artificial Intelligence: A How-To Guide

Artificial intelligence (AI) is bringing a sci-fi future to the present. This area of computer science, which aims to allow computers to think and perform tasks like a human, has evolved from an idea…to a chessmaster-defeating computer…to self-driving cars – all in a relatively short period of time. AI has the potential to impact every area of society, and its reverberations are already being felt in unexpected ways.

So, how can you take part in this exciting future?

Learn to Program

The foundations of AI lie in three areas: an ability to program, a basic understanding of machine learning, and a familiarity with bots. Learning a programming language, like Java, Python, Ruby on Rails, or C++ is an absolute necessity to a budding computer scientist – it provides the framework to build anything going forward.

An understanding of machine learning, a field of computer science that teaches computers to ‘learn’ by analyzing data without being specifically programmed by humans to do so, is equally important.

And finally, a familiarity with bots (which combine elements of these things) and how they work is also crucial. Bots are essentially computer assistants, ranging from simple chat interfaces to complex creations like Apple’s Siri or Amazon’s Alexa, that function using the basics of AI.

An understanding of all three of these areas is vital to learning artificial intelligence.

Take a Class

Some computer scientists went to school for their degrees; others are self-taught. Regardless of your education level, taking a class or two on AI can provide a solid understanding of the field. There are multiple online classes offered by prestigious institutions introducing this complex world. Stanford’s “Artificial Intelligence: Principles & Techniques” is one of the best, equipping students with the tools and knowledge to solve daily problems with AI. MIT’s Artificial Intelligence course teaches AI learning methods while breaking down the fundamentals of human intelligence for its students, lending useful perspectives for fledgling computer scientists.

Read about AI

Books and articles are plentiful, and often free resources for programmers of any experience level. Artificial Intelligence: A Modern Approach, by Stuart J. Russell and Peter Norvig, is available online, and offers coverage of the basics. Nils J. Nilsson’s The Quest for Artificial Intelligence is a great history lesson on AI from concept to present. Even Bill Gates has some recommendations on the subject: Nick Bostrom’s Superintelligence and Pedro Domingos’s The Master Algorithm are two of his favorite books about AI.

Tickeron has also created an elaborate online library covering many topics in AI, particularly in regards to the investment field. You can explore the library and blogs from experts on tickeron.com.

Attend Conferences

Conferences are an amazing resource for AI students. Much can be learned from the field’s leading lights as they gather to debate, analyze, and share the results of research and experience. For those who cannot attend a gathering in person, YouTube is full of great archival content from conferences, lectures, and more. It offers the chance to learn directly from some of the most intelligent people in the business, all from the comfort of your couch. Tesla and SpaceX’s Elon Musk has given numerous talks on the subject that novices might find interesting; his 2014 discussion at MIT and 2015 conversation at Samford University provide interesting perspectives on AI in a variety of industries.

Join the Tickeron Community

Tickeron has developed AI for investing. From the novice investor to the expert trader, a user can find AI tools on tickeron.com that can assist in the investment process. Beginners can use Tickeron’s Diversification Score tool to measure how well their current portfolio is diversified. Or, if you simply have cash and are looking for investment ideas, you can query Tickeron’s AI for suggestions.

On a more sophisticated level – but still very much user-friendly – traders can use Tickeron’s Pattern Search Engine, which is an AI tool designed to scan the stock, ETF, cryptocurrency, and forex markets for technical trading patterns. Tickeron’s AI is finding new patterns pretty much every day, and delivering trade ideas right into the inboxes of subscribers. Using Tickeron’s online tools is the equivalent of having an AI assistant, where algorithms do all the work.

The Future

AI has officially entered the mainstream. From ‘Google Now’ on our phones to self-driving cars on the roads to IBM’s Watson besting two previous Jeopardy champions, AI not only exists – it is here to stay. The field holds tremendous untapped potential even as it finds a place in our everyday lives. Use these tips as a guide and join the next generation of computer scientists, who will be instrumental in ushering in AI’s ever-evolving, very bright future.

Related Ticker: TSLA

Momentum Indicator for TSLA turns positive, indicating new upward trend

TSLA saw its Momentum Indicator move above the 0 level on February 14, 2024. This is an indication that the stock could be shifting in to a new upward move. Traders may want to consider buying the stock or buying call options. Tickeron's A.I.dvisor looked at 74 similar instances where the indicator turned positive. In of the 74 cases, the stock moved higher in the following days. The odds of a move higher are at .

Price Prediction Chart

Technical Analysis (Indicators)

Bullish Trend Analysis

The RSI Oscillator points to a transition from a downward trend to an upward trend -- in cases where TSLA's RSI Oscillator exited the oversold zone, of 28 resulted in an increase in price. Tickeron's analysis proposes that the odds of a continued upward trend are .

The Moving Average Convergence Divergence (MACD) for TSLA just turned positive on February 08, 2024. Looking at past instances where TSLA's MACD turned positive, the stock continued to rise in of 43 cases over the following month. The odds of a continued upward trend are .

Following a 3-day Advance, the price is estimated to grow further. Considering data from situations where TSLA advanced for three days, in of 346 cases, the price rose further within the following month. The odds of a continued upward trend are .

Bearish Trend Analysis

The Stochastic Oscillator has been in the overbought zone for 1 day. Expect a price pull-back in the near future.

The 50-day moving average for TSLA moved below the 200-day moving average on February 01, 2024. This could be a long-term bearish signal for the stock as the stock shifts to an downward trend.

Following a 3-day decline, the stock is projected to fall further. Considering past instances where TSLA declined for three days, the price rose further in of 62 cases within the following month. The odds of a continued downward trend are .

TSLA broke above its upper Bollinger Band on February 15, 2024. This could be a sign that the stock is set to drop as the stock moves back below the upper band and toward the middle band. You may want to consider selling the stock or exploring put options.

The Aroon Indicator for TSLA entered a downward trend on February 14, 2024. This could indicate a strong downward move is ahead for the stock. Traders may want to consider selling the stock or buying put options.

Fundamental Analysis (Ratings)

Fear & Greed

The Tickeron SMR rating for this company is (best 1 - 100 worst), indicating strong sales and a profitable business model. SMR (Sales, Margin, Return on Equity) rating is based on comparative analysis of weighted Sales, Income Margin and Return on Equity values compared against S&P 500 index constituents. The weighted SMR value is a proprietary formula developed by Tickeron and represents an overall profitability measure for a stock.

The Tickeron Profit vs. Risk Rating rating for this company is (best 1 - 100 worst), indicating well-balanced risk and returns. The average Profit vs. Risk Rating rating for the industry is 83, placing this stock slightly better than average.

The Tickeron Seasonality Score of (best 1 - 100 worst) indicates that the company is fair valued in the industry. The Tickeron Seasonality score describes the variance of predictable price changes around the same period every calendar year. These changes can be tied to a specific month, quarter, holiday or vacation period, as well as a meteorological or growing season.

The Tickeron Price Growth Rating for this company is (best 1 - 100 worst), indicating fairly steady price growth. TSLA’s price grows at a lower rate over the last 12 months as compared to S&P 500 index constituents.

The Tickeron PE Growth Rating for this company is (best 1 - 100 worst), pointing to worse than average earnings growth. The PE Growth rating is based on a comparative analysis of stock PE ratio increase over the last 12 months compared against S&P 500 index constituents.

The Tickeron Valuation Rating of (best 1 - 100 worst) indicates that the company is significantly overvalued in the industry. This rating compares market capitalization estimated by our proprietary formula with the current market capitalization. This rating is based on the following metrics, as compared to industry averages: P/B Ratio (10.256) is normal, around the industry mean (6.077). P/E Ratio (46.919) is within average values for comparable stocks, (18.348). Projected Growth (PEG Ratio) (2.366) is also within normal values, averaging (5.476). TSLA has a moderately low Dividend Yield (0.000) as compared to the industry average of (0.043). P/S Ratio (7.267) is also within normal values, averaging (37.052).

Notable companies

The most notable companies in this group are Tesla (NASDAQ:TSLA), Ford Motor Company (NYSE:F), General Motors Company (NYSE:GM), NIO Inc. (NYSE:NIO).

Industry description

Automobiles continue to be arguably the most popular form of passenger travel in the U.S., and major automobile makers have revenues and market capitalizations running into multi-billions. In recent years, the industry has been experiencing some path-breaking innovations like electric vehicles and self-driving technology. While there are long-standing companies like General Motors, Ford, and Toyota Motors operating in this space, there are also emerging/rapidly growing players like Tesla – which has had a major role in the growing popularity of the electric vehicle market. With technological advancements taking steam in the auto space, we’ve also witnessed collaborations (or talks of potential partnerships) of carmakers with tech behemoths like Google’s subsidiary, Waymo.

Market Cap

The average market capitalization across the Motor Vehicles Industry is 33.63B. The market cap for tickers in the group ranges from 1.56M to 642.53B. TSLA holds the highest valuation in this group at 642.53B. The lowest valued company is VLCN at 1.56M.

High and low price notable news

The average weekly price growth across all stocks in the Motor Vehicles Industry was 4%. For the same Industry, the average monthly price growth was 2%, and the average quarterly price growth was -13%. ARVLF experienced the highest price growth at 77%, while NWTN experienced the biggest fall at -55%.

Volume

The average weekly volume growth across all stocks in the Motor Vehicles Industry was 4%. For the same stocks of the Industry, the average monthly volume growth was 18% and the average quarterly volume growth was 68%

Fundamental Analysis Ratings

The average fundamental analysis ratings, where 1 is best and 100 is worst, are as follows

Valuation Rating: 45
P/E Growth Rating: 73
Price Growth Rating: 58
SMR Rating: 67
Profit Risk Rating: 83
Seasonality Score: 1 (-100 ... +100)
View a ticker or compare two or three
TSLADaily Signal changed days agoGain/Loss if shorted
 
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A.I.Advisor
published price charts
A.I. Advisor
published General Information

General Information

a manufacturer of electric sports cars

Industry MotorVehicles

Profile
Fundamentals
Details
Industry
Motor Vehicles
Address
1 Tesla Road
Phone
+1 512 516-8177
Employees
140473
Web
https://www.tesla.com
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TSLA and

Correlation & Price change

A.I.dvisor indicates that over the last year, TSLA has been loosely correlated with STLA. These tickers have moved in lockstep 46% of the time. This A.I.-generated data suggests there is some statistical probability that if TSLA jumps, then STLA could also see price increases.

1D
1W
1M
1Q
6M
1Y
5Y
Ticker /
NAME
Correlation
To TSLA
1D Price
Change %
TSLA100%
-0.14%
STLA - TSLA
46%
Loosely correlated
+0.31%
LCID - TSLA
43%
Loosely correlated
+2.79%
RIVN - TSLA
42%
Loosely correlated
+0.09%
NIO - TSLA
38%
Loosely correlated
+5.89%
RACE - TSLA
38%
Loosely correlated
-0.88%
More
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